Below is a list of investigators who are specifically interested in recruiting new HST students to their labs, together with sample project descriptions. Enrolled HST students are welcome to contact these faculty members as well as many others with laboratories at MIT, Harvard, affiliated hospitals and research institutes.

Omar Abudayyeh | Jonathan Gootenberg - Abudayyeh-Gootenberg Lab

gene and cell therapy, CRISPR, therapeutic delivery, aging, synthetic biology, machine learning, climate change/sustainability, technology development, cell reprogramming

Current Projects:

New gene editing tools
Through mining bacterial and eukaryotic genomes, we have multiple projects uncovering novel proteins and enzymes to precisely alter DNA and RNA. Through biochemical characterization and protein engineering, we are developing these tools for new classes of gene and cell therapy. 

Nucleic Acid Delivery
Ensuring the efficient delivery of nucleic acids into cells beyond the liver is critical for developing new gene and cell therapies. Our lab is leveraging the natural biology of nanoparticles and protein engineering to develop programmable delivery solutions that can reach extra-hepatic tissues, like the lungs, brain, bone marrow and more. 

Aging Reversal
The mysteries of aging are no longer impenetrable as we delve deeper into cellular and molecular mechanisms. We are using novel molecular tools and approaches our lab has developed over the past few years to build better molecular signatures of aging and new ways to partially reprogram diverse tissues. 

Large language models for directed evolution and cell design
Methods for rational engineering of mutations, fusions, and activities on existing protein families. Computational discovery of novel programmable protein tools. Application of these methods to genome editing, therapeutic delivery, diagnostics, and sustainability/climate change

Cell reprogramming
New approaches for generating and engineering specific cell types and states, using combinations of transcription factors, small molecules, and other perturbations. Novel molecular tools for sensing and responding to cell types and states in vitro and in vivo. Computational methods for rationally engineering cell transitions

Contact: hello-abugoot [at]

Location: MIT and Longwood

Iman Aganj - Laboratory for Computational Neuroimaging (LCN)

medical image segmentation, brain connectivity analysis

Current Projects:

Medical image segmentation
We'd like to use computational analysis to segment brain structures, such as the locus coeruleus, from available T1/T2/diffusion MRI images.

Brain connectivity analysis
We'd like to find relationships between structural and functional connectivity of the human brain and neurodegenerative disease.

Code optimization
We'd like to optimize existing code so they run faster on CPU and GPU.  

Contact: iaganj [at]

Lab Location: Charlestown

Daniel G. Anderson - MIT Koch Institute

nano medicine, biomaterials, drug delivery, mRNA, genome editing

Current Project:

Non-Viral Gene Therapy
Our laboratory is working to expand the impact of non-viral gene delivery, by improving mRNA vaccines, increasing the tissues where mRNA therapy can have an impact, and developing non-viral, genome editing approaches. A variety of projects are available in this area for those interested in developing a multidisciplinary thesis project in non-viral gene therapy for a range of human diseases

Contact: dgander [at] | Tara Fawaz, tafawaz [at]

Lab Location: MIT - Koch Institute

Soheil Ashkani - FARIL-MGH

Orthopaedic surgery, foot and ankle research, artificial intelligence, patient specific instruments, 3D modeling, clinical research, machine learning, medical entrepreneurship, ultrasound, medical imaging

Current Projects:

The use of AI in Orthopaedic Surgery
We use various AI methods to improve the quality of healthcare in orthoapedic surgery diagnosis, treatment, prediction of outcomes, and developing data registries. We turn our AI algorithms into applications and decision-support tools for our providers.

3D modeling and orthopaedic device development
We design novel devices for the treatment of orthpaedic patients, including patient-specific surgical tools, rehabilitation devices, and orthoses, using novel 3D printers we have in the lab.

Clinical Studies in Orthopaedics
Clinical studies, including retrospective studies, prospective trials, and review articles, are being conducted in our lab on various topics in the realm of orthopaedic practice.

Novel Imaging methodologies
We use novel imaging techniques, including portable handheld ultrasound devices, weight-bearing bilateral CT scans, novel needle arthroscopy, and portable thermography imaging, to improve the accuracy, speed, and access to diagnostic methods for our providers. We combine these technologies with computer-assisted and AI-assisted interpretation.

Educational initiatives
We produce educational videos, podcasts, articles, and social media content on various topics in orthoapedic surgery in order to educate and train our trainees and to inform our patients regarding their pathologies, treatment, prevention, and rehabilitation methods.

Contact: sashkaniesfahani [at] mgh.harvard.edusyeates [at]

Location: Weston

Sylvan Baca - Computational Cancer Epigenomics

Computational epigenomics, liquid biopsy, cancer, machine learning

Our lab applies develops and applies computational methods, with a focus on epigenomics, to advance precision oncology. We have several projects that are well-suited to students with a strong background in R and/or python. 

Current Projects:

Analysis of novel liquid biopsy datatypes
We are analyzing epigenetic features of cell-free DNA to learn about non-mutational mechanisms of treatment resistance in cancer. (eg:

Cistrome-wide associations studies
We are applying a method for understanding how GWAS variants influence cancer risk through effects on the epigenome. (eg:

We are developing methods to learn epigenomic features of cancer from DNA fragmentation patterns in clinical cancer specimens.

Contact: sbaca [at] | Lauren Stone, Lauren_Stone [at]

Location: Longwood

Alejandro Balazs - Balazs Lab

HIV, SARS-CoV-2, Antibodies, AAV, Gene Transfer, Vectored ImmunoProphylaxis

Current Projects:

Engineering Immunity against HIV
Using AAV to deliver broadly neutralizing antibodies as a means of preventing or treating HIV infection.

Development of polyclonal vectored immunoprophylaxis
Using AAV vectors to engineer the delivery of bi-specific antibodies with novel capabilities against HIV.

Understanding AAV immunogenicity 
Exploring the immunology of gene transfer and approaches to minimize host response against it.

Contact: abalazs [at]

Lab Location: Ragon Institute 

Daniel Bauer - Bauer Lab

Therapeutic genome editing, functional genomics, nuclease editing, base editing, prime editing, CRISPR screens, hematopoiesis, hematopoietic stem cells, globin gene regulation, hemoglobin switching, blood disorders, hemoglobinopathies, sickle cell disease

Current Projects:

Therapeutic base and prime editing in hematopoietic stem cells to correct, ameliorate, or enhance blood cell functions. Studies range from technology development to target discovery to preclinical validation to first-in-human proof-of-concept.

Nucleotide-resolution functional genomics to identify novel mechanisms of hematopoiesis and targets for blood disorders. Pooled screens with single cell and in vivo readouts.

Manipulation of hematopoietic stem cells to enable therapeutic genome editing without chemotherapy. 

Key collaborations include Pinello (computational biology), Genovese (hematopoietic engineering), Manis (HSC collection) labs.

Contact: daniel.bauer [at]

Lab Location: Longwood (BCH)

Ross Berbeco - Berbeco Lab

nanoparticles, imaging, radiation, MRI, x-ray

Current Projects:

Preclinical and clinical radiation therapy and imaging with novel nanoparticles
We are developing new nanoparticles for combination imaging (e.g. MRI, x-ray) and radiation therapy applications. One nanoparticle is in Phase 2 clinical testing at our institution and others are currently being evaluated pre-clinically. Projects can include lab bench work, animal research, computational studies, and image analysis.

Preclinical and clinical multi-energy imaging with novel detectors
We are engaged in the design, development, testing, and clinical evaluation of novel multi-layer flat-panel imagers for multi-spectral applications. Projects include Monte Carlo simulations, reconstruction algorithm design, and image analysis.

Contact: ross_berbeco [at]

Lab Location: Longwood

Alejandro Bertolet - b-lab

Radiopharmaceuticals, Computational Modeling, Radiation Biology

Current Projects:

A computational tumor model for Glioblastoma Multiforme (GBM)
To develop an innovative and complex approach to model the evolution of glioblastoma multiforme tumors. We will use a novel agent-based model to incorporate specific mechanisms specific to GBMs, helping treatment design and optimization.

Personalizing Y90-microsphere treatment for transarterial radioembolization in liver cancer
We are working on a novel treatment planning system, with two main aspects to be further developed: (i) our current adult human liver phantoms models must be replaced by patient-specific data, and (ii) microspheres must be statistically distributed around the tumor and arteriovenous junctions in the normal tissue. Then, a dose calculation algorithm like Monte Carlo can be integrated into the MIDOS model.

Modeling radiation-induced damage repair
How the DNA damage induced by radiation is repaired is a key factor in determining cell fate. We have recently developed a Monte Carlo-based model to simulate repair mechanisms according to a set of parameters. The student will be responsible for: collecting data from the literature showing DNA damage repair after controlled irradiations, finding the right values for the parameters in our model to reproduce observed experiments, and simulating the effects of different radiation types over several cell lines.

Contact: abertoletreina [at] | Carlos Huesa-Berral, chuesaberral [at]

Lab Location: MGH Main Campus

Berkin Bilgic - BRAIN lab

MRI, medical imaging, deep learning, AI

Current Projects:

We develop data acquisition and image reconstruction strategies that synergistically employ MR physics, cutting edge hardware, signal processing and deep learning algorithms to push the limits of spatial and temporal resolution for more efficient clinical and neuroscientific imaging. 

Contact: bbilgic [at]

Location: Charlestown

Lydia Bourouiba - Fluids and Health Network

Fluid physics, biophysics, physiology, infectious diseases, ecology and evolution, devices, monitoring, personalized medicine

Who we are: The Fluid & Health (FH) Network at MIT is an intellectual community of faculty, students, and staff interested in long-standing challenges at the intersection of fundamental fluid physics, health/disease, and environmental applications. To solve such grand challenges, new fully integrated and multidisciplinary approaches are needed that draw from the relevant basic science disciplines (physics, mathematics, biology, chemistry) to develop novel methodologies, tools, and engineering solutions. The FH Network brings together such rich combination of fields participating laboratories to enable uniquely stimulating and creative intellectual exchanges to accelerate problem solving and provide for an open-learning environment that transcends the traditional boundaries of the typical single PI.

Projects and scope:  
All our projects emerge from the interaction and exchanges between the team at large, and evolve over time as data and insights are generated. Current projects include:

- Novel approach for dehydration monitoring: Vulnerable populations, especially the elderly, are at risk of dehydration.  A means for monitoring the hydration status of a person quantitatively is currently lacking, though such a technology has the potential to prompt people and their caregivers to take action to eliminate the incipient risk.

- Approaches for detecting, characterizing and sizing of emboli (blood clots or gaseous bubbles) in high-risk hospital populations. Emboli can lead to major adverse health events, such as neurocognitive impairment or stroke. Unfortunately, such emboli still occur routinely in patients put on life-saving therapies, such as ventricular assist devices and extracorporeal membrane oxygenation. A continuous monitoring method to detect such emboli is currently not available in routine clinical care.

- Critical insights about pathogen transmission from host to host (taken from the view point of the pathogen).  These insights derive from an integration of biophysics and infectious disease perspectives leveraging pathogen "-omics", fluid physics, microfluidics, optics, and electrical and mechanical instrumentation.

- Deepening our understanding of how respiratory pathogens (e.g TB, COVID) interact with host physiology using both experimental and theoretical approaches to solve major open puzzles on key processes emerging from the interaction of host physiology, pathogen, and environment, and how they drive evolution of pathogens and their transmission and thus can inform out-of-the-box innovative new controls and drug development.

Mentees we seek: This work requires intrepid learners who like to pioneer and take uncharted paths for innovation and wish to draw from and grow in multiple scientific disciplines while being solidly grounded in one field to help solve real societal problems.  If you are interested in problems that somehow relate to fluids and health please reach out.

Lab Locations: MIT, collaborating Boston hospitals depending on project specifics.

Integrative Neuromonitoring and Critical Care Informatics Group,



Lydia Bourouiba lbouro [at] (lbouro[at]mit[dot]edu) | Martha L Gray mgray [at] (mgray[at]mit[dot]edu) | Thomas Heldt thomas [at] (thomas[at]mit[dot]edu)

Christopher Cassa - Cassa Lab

Making integrated predictions of clinical risk, approaches to assess variant functional effects with population data and high-throughput CRISPR functional assays, large language models

Current Projects:

Integrated predictions of clinical risk: 
Patients who carry rare variants in established disease genes (e.g. BRCA1, LDLR) may have increased risk for the related clinical disorders. However there are many other factors which can influence clinical risk, including polygenic risk, clinical risk factors, and behavioral/environmental/lifestyle risk factors. We develop integrated clinical risk models which draw on these sources of information. 

Approaches to assess variant functional effects: 
We develop integrated models to assess variant functional effects using population data, computational predictions of functional effect, and functional data from high-throughput CRISPR assays. These are useful for improving assessment of variant pathogenicity, but also for identifying new genes which may affect a trait or cause a disease. 

Evidence standards for variant classification (e.g. determining whether a variant is classified by a clinical lab as pathogenic), and communicating information about genomic risk.

Contact: ccassa [at]

Lab Location: Longwood (HMS NRB)

Ciprian Catana - Integrated PET-MR Imaging Laboratory

multimodality imaging, PET-MRI, quantification, machine learning, neuroscience, cancer, lung fibrosis

Current Projects:

Development of the Human Dynamic Neurochemical Connectome Scanner
The goals of this project are to build, integrate and test the hardware and software components for a next-generation 7 Tesla MR-compatible PET insert with dramatically improved sensitivity and perform proof-of-principle studies in healthy volunteers.

PET-MR Imaging of pulmonary fibrosis
This project aims to apply PET-MR imaging to quantify molecular abnormalities in the lungs of idiopathic pulmonary fibrosis patients and determine if such measures can predict the pace of disease progression and determine whether the patient is responding to anti-fibrotic therapy.

Contact: ccatana [at]

Lab Location: Charlestown

Elliot Chaikof - Chaikof Lab

drug delivery, drug discovery, tissue engineering, genome engineering, innate and adaptive immunity, artificial organs

Current Projects:

Delivery Technologies
Developing protein-based nanoparticles for efficient delivery of therapeutic macromolecules. We are developing protein polymer-based, cell type-specific delivery systems to enhance the efficacy and safety of genome editors, RNA therapeutics, and other macromolecular cargo for in vivo applications, including the treatment of inherited hematopoietic disorders and the design of immuno-oncology therapeutics.

Engineering Living Tissues
Cell and tissue engineering for applications in regenerative medicine. We are investigating genetic pathways that could serve as rational targets to improve the long-term success of organ, tissue, and cell transplantation through multiplex genome editing and developing new additive manufacturing approaches to accelerate organ fabrication. Areas of focus include the development of immunoevasive (hypoimmunogenic) living blood vessels.

Modulating Innate Immunity
Defining modulators of innate immunity and tissue repair. We are studying transcription factor protein-protein interactions that promote gut tissue integrity and are developing small molecules that target these interactions as immune-modulating therapeutics with relevance to inflammatory bowel disease and other disorders. Areas of focus include regulatory T cell modulators.

Glycobiology & Glycotherapeutics
Defining Clinically Relevant Protein-Glycan Interactions. We are developing tools to study the roles of glycan-protein interactions in innate immunity, thrombosis, and cancer and identifying molecules that target these interactions as therapeutic agents. We hope to decipher underlying mechanisms of cancer-associated venous thromboembolism

Biologically Inspired Artificial Organs
Biomolecular engineering to improve the performance of implanted cardiovascular devices and other blood contacting artificial organs. We are developing schemes that regenerate selective bioactive molecular constituents after device implantation to extend the lifetime of anti-thrombogenic films and enhance clinically related performance characteristics of blood contacting devices.

Contact: echaikof [at]

Lab Location: Longwood

Yee-Ming Chan - Pediatric Reproductive Hormone (PReproHormone) Program

pediatric reproductive endocrinology, delayed puberty, differences of sex development, transgender health

Current Projects:

Genetics of delayed puberty
We are studying the role of both common and rare genetic variants in causing self-limited delayed puberty (constitutional delay of puberty) to understand the pathways that determine pubertal timing.  We are also using genetic instruments to assess the effects of pubertal timing on adult health.

Genetic testing for differences of sex development (DSD)/intersex conditions
We are analyzing rare-variant causes of DSD's and also studying the impact on parents of receiving genetic testing results.

Physical effects of gender-affirming hormonal treatments
As part of the four-site Trans Youth Care (TYC) study, our group is analyzing data from the largest longitudinal cohort in the US of transgender and nonbinary youth receiving hormonal treatments for gender affirmation (GnRH agonists for pubertal blockade and sex steroids for pubertal induction). Our site is focusing on physical outcomes (growth, bone mineralization, metabolic changes), and other investigators are focusing on psychosocial outcomes.

Contact: Yee-Ming.Chan [at]

Lab Location: Longwood

Luke Chao - Chao Lab

Structural Biology, Biophysics, in vitro reconstitution, cryo-EM, cryo-ET

We are a group of structural biologists, biochemists & biophysicists interested in how cellular membrane form and function is shaped by large protein assemblies. We ask questions in diverse systems ranging from bacterial cell wall biogenesis (Navarro, Vettiger et al. PMID: 36097171) to plasma membrane projects. A focus area of particular interest is mitochondrial morphology.

We have tackled questions of mitochondrial form/function in studies of how inner-membrane fusion is regulated using in vitro reconstitution/TIRF microscopy approaches (Ge et al., PMID: 31922487), and how cristae shape is regulated using cryo-ET (Fry, Navarro et al., PMID: 36711707). We are also interested in using molecular phylogenetics and protist diversity to explore the evolution of mitochondrial shaping proteins.

A potential project: in vitro reconstitution of a mitochondrial crista junction. 
The cristae junction (CJ) is a membrane neck that stabilizes the mitochondrial inner-membrane folds. The CJ is serves as a nexus of the organelle's diverse functions. How protein assemblies cooperate to mediate this enigmatic membrane structure remain unclear. To answer these questions you will have the opportunity to explore in vitro reconstitution and cryo-EM/ET approaches to understand principles for CJ stabilization and dynamics.

The long-term potential impact from our studies is fundamental understanding for rationale engineering of organelle structure & function.

Contact: luke [at]

Lab Location: MGH Main Campus


Jingyuan Chen - CANDY Lab

multi-modal imaging, signal processing, brain dynamics

Current Projects:

Method development for multi-modal neuroimaging
This project aims to optimize the methodology of functional PET imaging and its fusion with simultaneous (EEG-)fMRI. 

Metabolic signatures of brain network dynamics 
This project employs simultaneous PET-MRI to characterize how global and local cerebral glucose metabolism redistributes across different cognitive and arousal conditions.

Contact: jechen [at]

Lab Location: MGH Martinos Center, Charlestown

Adrian Dalca

machine learning, deep learning, generative AI, medical images

Current Projects:

Large machine learning models for solving multiple imaging tasks
We are working on ways to integrate information across different processing tasks and datasets to solve multiple popular/important imaging tasks (segmentation, registration, diagnosis) at once, improving easy of use, accuracy, speed, and data dependency.

Integrating language and imaging for improved image analysis pipelines
An ongoing project merges natural language and image features together to facilitate robust and easily interactive models that carry out and generalize to a wide array of medical image processing and analysis tasks

Machine learning models for general rapid interactive segmentation
We are designing new interactive systems that enable very fast and easy manual segmentation pipelines of *any* medical image. The systems will learn across domains to rapidly predict what a user is trying to segment as they segment.

Integrating anatomical or clinical knowledge in machine learning models
We are working on general ways to integrate medical knowledge and external clinical attributes into deep learning models for various analyses.

Contact: adalca [at]

Lab Location: Charlestown, MIT

George Daley - Daley Lab

Stem cells, cancer, hematopoiesis

Current Project:

Our laboratory seeks a better understanding of the biology, pathology, and clinical utility of hematopoietic and pluripotent stem cells and of the role of various tissue stem cells in development and disease. We focus our studies on murine and human blood development and on common mechanisms of stem cell biology and cancer. Our goals are to define fundamental principles of how stem cells contribute to tissue regeneration and repair and to improve drug and transplantation therapies for patients with malignant and genetic bone marrow disease.

Contact: George.daley [at]

Lab Location: Boston Children's Hospital

Alan D'Andrea - D'Andrea Laboratory

Cancer Research, Chromosome Instability, AntiCancer Drug Screening, DNA Repair

Multiple projects available relevant to key research areas, please contact for more details.

Contact: alan_dandrea [at]

Lab Location: Longwood

Brandon J. DeKosky - Immune Engineering Lab

​​​​​​​B cell receptors, T cell receptors, single-cell analysis, infectious diseases, high-throughput screening, infectious diseases, cancer therapeutics

Current Projects:

High-throughput antibody screening technologies and computational approaches for rapid drug discovery
The current low-throughput technologies used for antibody discover cannot deconvolute the molecular features of human immunity against the vast array of potential protein targets. This project will develop and implement new experimental and/or machine learning/AI approaches to comprehensively characterize human antibody immunity, and for improved drug discovery including against global infectious diseases and pandemic health threats.  

Personalized T cell receptor therapies for cancer cures
T cells are known to protect effectively against cancers, but the identification of T cell receptors as drugs for individual patients remains too difficult for clinical use. This project will establish a rapid technology to screen and identify protective T cell receptors, and apply it to understand the key features of anti-cancer immune pressure in human patient cohorts and in relevant animal models that recapitulate critical aspects of human disease.

Contact: dekosky [at]

Lab Location: MIT / The Ragon Institute

Darin Dougherty - Division of Neurotherapeutics, Department of Psychiatry

Neuromodulation, Focused Ultrasound, Neuroimaging, Obsessive-Compulsive Disorder, Generalized Anxiety Disorder

Low-intensity/transcranial focused ultrasound is a novel form of noninvasive brain stimulation that has the potential to stimulate brain regions deep in the brain without the risks and side effects of neurosurgery. Our lab is conducting several studies investigating its therapeutic potential for treatment-resistant OCD and GAD

Current Projects:

Imaging-guided Low-Intensity Focused Ultrasound (LIFU) Neuromodulation of Ventral Striatum in Obsessive-Compulsive Disorder (OCD)

Clinical Feasibility of Low Intensity Focused Ultrasound Pulsation for the Treatment of Generalized Anxiety Disorder

Contact: ddougherty [at] | Director of Research: Tina Chou, PhD, tchou [at]

Lab Location: Charlestown Navy Yard-MGH

Pierre Dupont - Medical Rbootics & Interventional Devices

robotic catheters, transcatheter heart valve repair & replacement

Current Projects:

Robotic Cardiac Catheters 
We are developing robotic catheters for heart valve repair and for treatment of arrythmias. Robotics offers the advantage of reducing the learning curve for complex beating-heart procedures and, ultimately, provides a platform for introducing automation. Important components of these projects can include algorithmic catheter design, catheter modeling and control, integration of multi-modal sensing, integration of therapeutic devices, and testing in anatomical models and animal models.

Transcatheter Heart Valve Repair and Replacement Devices 
Transcatheter procedures avoid the trauma and risks of open-heart surgery by delivering devices that are intended to replicate surgical repair and replacement. We are creating novel devices and tools for both valve repair and replacement. These projects require innovative design and creative problem-solving skills. 

Cutting tools for Transcatheter Valve Modification 
While current transcatheter valve interventions deploy devices that push, pull and approximate tissue to restore valve function, a complete surgical repair often involves cutting and removing valve tissue. As a first step toward providing this capability, this project will involve developing catheter-delivered energy-based cutting tools for valve repair and replacement. Components of the project can include creating an automated tool evaluation testbed, characterizing the effect of cutting parameters on the distribution of potentially-embolic cutting debris, catheter integration of the tools and in vivo testing. 

Contact: [at]

Lab Location: Longwood

Shadi A. Esfahani - Molecular Theranostics Lab and Center for Precision Imaging

Theranostic, Cancer, PET imaging, SPECT imaging, Cancer therapy, Molecular Probes, Tumor Biomarkers

Current Projects:

Development and application of novel molecularly targeted PET imaging probes for improved detection and characterization of cancers. The student will learn about the development of new antibody, peptide, nanobody and liposomal-based molecular imaging probes, and their application for the detection of tumors in cells and animal models. 

Molecular Theranostics of Cancer:                                                 Novel molecular probes will be developed for both detection and treatment of different types of cancers, based on the specific biomarker(s) in the tumors. Students will learn variable techniques such as cell culture, tissue staining, model development, biodistribution, PET and SPECT image acquisition and analyses, flowcytometry, chemotherapy, radiotherapy, and immunotherapy. 

Hyperpolarized MR spectroscopic imaging of cancer: 
This will involve studying the role of changes in tumor metabolic pathways for early evaluation and prediction of response to treatment in cancer cells and models.  

Contact: esfahani.shadi [at] 

Lab Location: Charlestown

Christian Farrar - Farrar Lab

MRI, molecular imaging, machine learning, magnetic resonance fingerprinting

Current Projects:

Artificial Intelligence Boosted Evolution and Detection of Genetically Encoded Reporters for In Vivo Imaging
Cell and viral based therapies have the potential to revolutionize the treatment of many diseases. However, the optimization of such biological therapies depends critically on the ability to monitor the spread and persistence of the therapeutic agent and assess the tissue response. This project is focused on developing and optimizing a novel MRI reporter gene technology that allows for the imaging of cell and viral based therapeutics. A novel genetic programing AI has been developed to help predict the optimal reporter protein sequence and structure. The reporter gene technology will be demonstrated for monitoring oncolytic virotherapy in glioblastoma tumor models, however, the technology is generalizable to any cell or viral therapeutic.

Rapid and Quantitative CEST Imaging with Deep-Learning Magnetic Resonance Fingerprinting
Measurement of tissue pH and protein/metabolite concentrations using chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) has been demonstrated to provide crucial insight into many disease pathologies, including tumors, stroke, renal disease, osteoarthritis, and heart failure. However, clinical translation of these CEST-MRI methods has been hindered by the qualitative nature of the image contrast, the long image acquisition times, and the complex data processing required. This project is focused on developing, optimizing and translating to the clinic a novel Magnetic Resonance Fingerprinting (MRF) method that allows for rapid and quantitative pH and protein/metabolite imaging. A machine learning algorithm is being developed for optimizing the MRF acquisition protocol and maximizing the discrimination of different tissue pH and protein/metabolite concentrations.

Contact: cfarrar [at]

Lab Location: Charlestown Navy Yard

Bruce Fischl - Laboratory for Computational Neuroimaging

Neuroimaging analysis, machine learning, image processing, neuroscience

Current Project:

Registration, segmentation and synthesis of brain imaging data.

Contact: fischl [at] nmr.mgh.harvard.eduADALCA [at] MGH.HARVARD.EDU

Lab Location: Charlestown

Guillermo Garcia-Cardena

cardiovascular, mechanobiology, organoids, drug discovery

Our laboratory has multiple projects available for dissecting and probing signaling pathways critically important for the function of blood vessels. The ultimate goal of this efforts is the discovery of novel therapeutics for the treatment of cardiovascular disease. 

Current Projects:

Identification of novel cellular mechanosensors. 
This project seeks to identify novel mechanosensors activated in cells in response to flow. It combines a genome-wide CRISPR and small molecule screens with the use in vitro flow systems and mouse models.

Developing new systems to study interactions between blood vessels and cardiac muscle. 
This project aims to developed cardiac organoids generated with iPSC-derived cells cardiovascular with a perfused vasculature. It involves the use regenerative biology experimental platforms, microfluidics, and single-cell RNAseq. 

Contact: guillermo_garcia-cardena [at]

Lab Location: Longwood

Christopher Garris - Garris Lab

Cancer, Myeloid, Immune, Immunotherapy

Current Project:

Developing localized immunotherapies for bladder cancer treatment.

Contact: cgarris [at]

Lab Location: MGH Main Campus

Georg Gerber - Computational (micro)biology Lab

machine learning, deep learning, computational biology, microbiome, infectious diseases, statistics, time-series, dynamical systems, computer science, mathematics, microbiology, immunology

Current Projects:

Host immune system-microbiome interactions
Although host-bacterial interactions have been extensively characterized for some pathogens, much less is known about how commensal bacteria in the microbiome interact with us. A new focus in the lab will use both experimental systems (e.g., gnotobiotics) and computational approaches to study various aspects of immune host system-microbiome interactions, including influence on infection/inflammation and immune repertoire development/diversity. Funded positions for graduate students with either/both experimental and computational interests in this area are currently available.

Deep learning for the microbiome
The microbiome, or trillions of microbes living on and within us, is a complex and dynamic ecosystem that is crucial for human health, and when disrupted may contribute to a variety of diseases including infections, arthritis, allergies, cancer, heart and bowel disorders. Funded positions for graduate students are currently available for developing and applying novel deep learning methods that will further understanding of the microbiome. Applications include forecasting microbial population dynamics in the gut for rational design of therapies, predicting the impact of the microbiome on the onset or progression of human diseases, elucidating host-microbial metabolic interactions, and discovering functions of uncharacterized microbial metabolites and proteins.

Contact: ggerber [at]

Lab Location: Longwood (Brigham and Women's Hospital)

Patricia E. Grant - Fetal Neonatal Neuroimaging and Developmental Science Center

fetal, neonatal, brain development, MRI, NIRS, MEG, machine learning, genetics

Current Projects:

Brain MRI analysis
Assessing differences in brain development during childhood for persons with congenital heart disease, from either retrospective clinical cohort or research study cohorts.

Brain connectivity analysis
Collaborative study to assess changes to the brain connectome among persons with congenital heart disease in a multimodal analysis that includes genetic sequencing data

Genetic variant modeling
Introducing patient variants in human induced pluripotent stem cells to assess impact on heart and brain progenitor populations

Contact: ellen.grant [at] childrens.harvard.edusarah.morton [at]

Lab Location: Longwood

Rajat Gupta - Cardiovascular Genetics

Cardiovascular genetics, functional genomics, GWAS, CRISPR screens

Current Projects: 

What are the cellular phenotypes that drive genetic risk of cardiovascular disease? 
We use CRISPR screens to identify the pathways regulated by multiple risk loci. First we used Perturb-seq to profile the shared transcriptional effects of CRISPR knockdown of 2000 genes in endothelial cells. Now we are using a technology called Cell Painting to profile the cellular effects of these same CRISPR perturbations. This project would be in close collaboration with the Broad Institute.

The pathogenesis of Cerebral Cavernous Malformations
This project will identify new mechanisms of this rare neurovascular disease. We have identified new mutations that regulate the complex of genes previously implicated in CCM disease. We will sequence patients/families with the disease, and model their mutations in stem cells. We will also test novel ERK5 PROTAC inhibitors developed by our collaborators at Stanford.

Contact: rgupta [at]

Lab Location: Longwood

Rajiv Gupta - AXIS Center

X-ray Imaging, Static CT, Phase-contrasst X-ray imaging

Current Projects:

The Static CT project is an effort to build a non-rotating computed tomography system.
In this project, we will be developing emitter arrays using nanostructured cathodes, and integrating these with detectors and read-out systems. Further work will focus on reconstruction techniques using finite numbers of projections for tomosynthesis. This project is hardware intensive, and will take place primarily at the MGH Charlestown Navy Yard Laboratory.

Contact: rgupta1 [at] mgh.harvard.educhynes [at]

Lab Location: Charlestown

Allison Hamilos - The Stochastic Cognition Lab

behavioral neuroscience, computational cognitive science, neurosurgery, mice

How do we choose when we can’t know the right answer, or the right answer might not even exist? The philosopher al-Ghazali reasoned free will lies in our ability to act under uncertainty, in situations where we can only pick “randomly” at best. Intriguingly, such (effectively) stochastic behavior may be the key to intelligence. Machine learning algorithms depend on stochasticity, and probabilistic cognitive models explain human reasoning in situations where artificial intelligence struggles. What neural mechanisms enable us to behave so spontaneously? Our lab aims to answer these questions by dissecting the role of neural circuits disrupted in neurological and psychiatric disease. Drawing on clinical insight and intuition, we train mice to do complex behaviors, do neurosurgeries to record and manipulate neural circuits with optogenetics, and use computational modeling to understand how these circuits give rise to spontaneous behavior. 

We have a small lab where you'll work side-by-side with the PI to design and do very cool behavioral neuroscience and computational cognitive science experiments with mice! We're looking for passionate, curious and meticulous students eager to learn. Neuroscience experience is great but not required--we will train you!

Current Projects:

Determining the neural circuit mechanisms of spontaneous behavior
We'll train mice to play video games and record/manipulate their neurons to understand how animals make spontaneous motor, cognitive and perceptual decisions under uncertainty.
a. Learn to build electronics and write code to run behavior rigs
b. Learn to do neurosurgeries in mice
c. Learn to train mice to play video games
d. Learn to apply electrophysiology, fiber photometry and optogenetics to dissect neural circuits in behaving animals
e. Learn advanced statistical methods and modeling

Determining the impact of biological sex differences in neurosurgical outcomes
We will test the hypothesis that female biological sex confers resilience to neurosurgical trauma, with the goal of elucidating biological pathways upregulated in resilient neurosurgery subjects to design therapies to improve neurosurgical and neurotrauma outcomes in all patients. 
a. Learn to do neurosurgeries in mice
b. Learn to apply deep learning methods to diagnose focal neurological deficits in mice and quantify progression to recovery
c. Learn to apply advanced statistical and molecular biology methods to identify pathways involved in traumatic resilience/susceptibility

Contact: ahamilos [at]

Lab Location: Whitehead Institute (MIT)

Tayyaba Hasan - Hasan Lab

Orthopaedic surgery, foot and ankle research, artificial intelligence, patient specific instruments, 3D modeling, clinical research, machine learning, medical entrepreneurship, ultrasound, medical imaging

Photodynamic therapy (PDT) is a photochemistry-based treatment and relies on the use of non-toxic light activatable photosensitizers (PS) which upon light activation confer toxicity via generation of reactive molecular species. The Hasan lab is interested in studying the local and systemic effects of PDT and the associated phenomenon of Photodynamic priming (PDP), where the microenvironment of the pathology is made susceptible to subsequent therapies including antibiotics (in case of infections), chemo- and immunotherapy (in case of cancer). PDP is an enabler of conventional treatments and has been established to make them more efficient. We use nanotechnology-based combination approaches to exploit the optical properties of photosensitizers as it allows for controlled release of multiple drugs and evaluate it on architecturally complex in vitro and in vivo disease models. The inherent fluorescent property of photosensitizers is also used for treatment guidance using sophisticated imaging systems (hyperspectral fluorescence endoscope/mobile phone-based devices), both preclinically and clinically. Photoacoustic imaging is used to enhance deep tumor detection and margin delineation for surgical guidance. The theranostic potential of photosensitizers is studied for quantitative evaluation of microbial infections (malarial/bacterial) and their targeted inactivation by PDT. This is achieved by novel chemistry such as β-beta-lactamase enzyme-activated-PS (beta-LEAP), by Super-hydrophobic devices to generate singlet oxygen for bacterial elimination without direct contact of the photosensitizer with tissues and with Quantum dot Light Emitting Diodes for irradiation to produce miniature wearable systems. 
In summary we focus on various aspects associated with photodynamic activation to develop effective treatments and monitoring strategies for various cancerous and infectious diseases. All projects are a part of this overall scope.

Contact: thasan [at] | lbmaddox [at]

Lab Location: 40 Blossom St, MGH 

Marie Hollenhorst - Hollenhorst Lab

glycobiology, platelets, hemostasis, thrombosis, chemical biology

Current Projects:

ABO Blood Type and the Hemostatic System
ABO blood type is associated with risk for bleeding and thrombosis (clotting). The reason for this epidemiologic association is incompletely understood. We hypothesize that ABO blood group antigens carried on hemostatic glycoproteins have an impact on the function of coagulation factors and platelets. We are working to determine the inventory of hemostatic proteins which carry ABO blood group antigens and how the function of these proteins is affected by ABO blood group status.

Platelet Glycans and the Anti-Platelet Immune Response
Glycans (carbohydrate polymers) on the surface of platelets play an important role in the immune response against platelets. We are working to determine how glycans on the platelet surface affect anti-platelet immune responses in diseases such as immune thrombocytopenia, post-transfusion purpura, and fetal/neonatal alloimmune thrombocytopenia.

Contact: mhollenhorst [at] | Letice Arthur: larthur5 [at]

Lab Location: Longwood

Jun Huh - Huh Lab

autism, Alzeheimer's, microbiome, neuroimmunology

Current Project:

Studying the modulatory roles of immune cells in influencing animal behaviors and memory in the context of neurological disorders and infectious diseases.

Contact: Jun_Huh [at]

Lab Location: Longwood

Juan E. Iglesias - Laboratory for Ex vivo Modeling of Neuroanatomy (LEMoN)

Neuroimaging, AI, low-field MRI, dementia, stroke

Current Projects:

Portable, Low Field Brain Magnetic Resonance Imaging (MRI) for Stroke and Dementia
We are developing machine learning techniques to improve image quality and extract morphometric measures in portable brain MRI, which has huge potential in underserved areas and acute imaging settings (e.g., stroke).

Generative models of pathology for clinical brain MRI analysis
Our group has recently developed machine learning techniques for image analysis of brain MRI scans of any resolution and contrast, which has finally enabled the analysis of scans from our hospital PACS. While these techniques work remarkably well, we have so far trained them with relatively normal anatomy. The goal of this project is to learn to synthesize pathology during training (e.g., tumors, strokes) in order to enable the application of our methods in the wild.

Contact: jei [at]

Lab Location: Charlestown

Felipe Jain - Depression Clinical and Research Program

digital phenotyping, depression, computational psychiatry, mHealth, mobile applications, psychotherapy, mood, mindfulness, caregiving

Current Projects:

Digital Phenotyping of Mood
Develop and validate algorithms to use passive smartphone sensors (e.g. GPS, accelerometer) to develop features that predict mood.  Research participants are drawn from extant observational datasets and ongoing randomized, controlled trials in the laboratory.

Create and validate an mHealth intervention
Use the labs' CareDoc platform to create an mHealth application capable of delivering self-help and other therapeutic information, delivering questionnaires, and obtaining objective passive sensor measurements.

The ultimate goal of the laboratory is to create just in time, closed-loop, adaptive interventions that modify therapy automatically based on participants' engagement and progress. 

Contact: felipe.jain [at]

Lab Location: Massachusetts General Hospital

Rakesh Jain - Edwin L. Steele Laboratories for Tumor Biology

tumor microenvironment, vascular biology, matrix biology, drug delivery, imaging, immunotherapy, molecular & cell biology, metabolism, brain tumors, pancreatic cancer, breast cancer, clinical translation

Current Project:

Targeting the tumor microenvironment to improve cancer treatment
Our research goals are (i) to understand how the abnormal tumor microenvironment confers resistance to various cancer treatments (e.g., molecular therapeutics, nanotherapeutics, radiation and immunotherapy), (ii) to develop and test new strategies to overcome this resistance, and (iii) to translate these strategies from bench to bedside through multi-disciplinary clinical trials in patients with brain, breast, pancreatic, colon and ovarian cancers. This tight integration between bench and bedside and application of engineering/physical science principles to oncology is a hallmark of our research.   

Contact: rjain [at] mgh.harvard.eduegarzon [at] (Elizabeth Garzon) 

Lab Location: MGH


Alan Jasanoff - Jasanoff Lab

brain, neural circuit, molecular imaging, probe chemistry, synthetic biology, fMRI

Current Projects:

Brain-wide analysis of neural mechanisms
We apply a suite of innovative imaging probes to analyze neural circuit function in rodents and primates. Our molecular tools (see project 2) are detectable by noninvasive neuroimaging methods like MRI and functional ultrasound imaging; they provide readouts about how cell populations and neurochemical factors work together to mediate integrated aspects of brain function. We have particular interest in studying brain-wide mechanisms of decision-making, sensory processing, and intrinsic signaling dynamics. 

Creation of molecular tools for next-generation neuroimaging
We develop a diversity of chemical, nanotechnological, and genetic imaging probes for analysis of molecular and cellular function in intact, living organisms. We bring these molecular imaging technologies from concept to in vivo utility, with a strong focus on neural systems research (see project 1). We are interested both in basic neuroscience applications in animals, and in translational paths that may permit studies of human brain dynamics at the molecular level.

Contact: jasanoff [at]

Lab Location: MIT

Meher Juttukonda - Cerebrovascular Aging and Spin Labeling (CASL) Lab

MRI, hemodynamics, vascular physiology, cerebrovascular disease, aging, Alzheimer's disease

Current Projects:

Cerebral hemodynamics in typical and abnormal aging:
The human brain requires a constant supply of oxygen and other nutrients delivered through the bloodstream. Our lab is interested in applying noninvasive MRI approaches to understand cerebral hemodynamic function in health and disease. Projects include measuring cerebral perfusion and vascular reserve in older adults to assess the impact of risk factors for vascular disease and Alzheimer's disease on cerebrovascular function.

Noninvasive detection of altered capillary hemodynamics:
Once oxygen-rich blood is delivered to the microvasculature, oxygen is offloaded from capillaries into brain tissue. Our lab is interested in noninvasive MRI approaches for detecting the presence of capillary flow disturbances. Projects include development of arterial spin labeling (ASL) approaches for better characterizing microvascular flow and investigating the impact on white matter lesion burden and progression.

Imaging white matter perfusion with high-field MRI:
White matter poses unique challenges to perfusion imaging due to a lower vascular density and longer arterial transit times compared to gray matter. Our lab is interested in developing ASL MRI at 7 Tesla to address these challenges. Projects include the development of ASL with dynamic shimming approaches through collaboration with investigators at the Martinos Center to better characterize white matter cerebrovascular physiology.

Contact: mjuttukonda [at]

Lab Location: Charlestown

Ursula Kaiser - Laboratory of Reproductive Neuroendocrinology

Neuroendocrinology, Reproduction, Puberty, Fertility, GnRH

Current Projects:

Deciphering the functional role of MKRN3 in puberty and reproduction
We have identified mutations in an imprinted gene, MKRN3, which encodes an E3 ubiquitin ligase, in association with central precocious puberty. Projects are available for students to: (1) Elucidate the potential roles of MKRN3 in neuronal development and synaptic plasticity, using genetically modified mouse models and human iPSC-derived hypothalamic cell models; (2) Examine candidate targets of MKRN3, including KISS1, NKB, IGF2BP1 and LIN28B, as well as novel mRNA targets using eCLIP (enhanced Cross-Linking and ImmunoPrecipitation), in the regulation of the reproductive axis; and (3) Identify new MKRN3 targets and leverage mutations in key protein domains identified in patients with CPP to investigate the roles of different MKRN3 domains in protein function. 

Reproductive biology of gonadotropin regulation
Gonadotropin-releasing hormone (GnRH) is secreted in a pulsatile manner from hypothalamic neurons, and varying GnRH pulse amplitudes and frequencies act on the pituitary to preferentially induce either luteinizing hormone (LH) or follicle-stimulating hormone (FSH) to regulate fertility and the menstrual cycle. Our goal is to identify the mechanisms of this hormone pulse frequency-dependent regulation.  Projects are available for students to: (1) Determine the relative contributions of GnRH signaling through specific GnRHR-coupled signaling in gonadotropes to polycystic ovarian syndrome (PCOS), using our previously generated genetically modified mice in a well-established model of PCOS; and (2) Determine the relative contributions of GnRH signaling through specific GnRHR-coupled signaling in gonadotropes to hypothalamic amenorrhea (HA), using our previously generated genetically modified mice in an established model of HA.

Identifying the functional roles of DLK1 and MeCP2 in puberty and reproduction
We have identified mutations in two additional genes, DLK1 and MeCP2, in association with central precocious puberty. DLK1 (Delta Like Non-Canonical Notch Ligand 1), also known as pre-adipocyte factor 1 (Pref-1) and associated with Temple Syndrome in humans, is a non-canonical ligand in the Notch signaling pathway. MeCP2 (Methyl-CpG-binding protein 2) is an X-linked gene associated with Rett syndrome in humans, encoding a chromatin-associated protein that regulates transcription. Projects are available to determine the mechanisms by which these two genes regulate the timing of puberty, using mouse models as well as in vitro approaches.

Contact: ukaiser [at] | Dr. Rona Carroll, rcarroll [at]

Lab Location: Longwood

Sanjat Kanjilal

machine learning; infectious diseases; antibiotic resistance; clinical prediction modeling; causal inference

Current Projects:

Foundation models in health care                                                                             Use of large language models for medical history summarization for patients with complex infection

Federated machine learning 
Development of federated (ie privacy-protected) learning methods for large scale ML using multicenter datasets for various tasks related to predictive modeling and causal inference in infectious diseases

ML prediction models using raw clinical equipment data for rapid identification of bloodstream pathogens and antibiotic susceptibility

Contact: skanjilal [at]

Lab Location: Longwood

Kristin Knouse - Knouse Lab

technology development, high-throughput functional genomics, in vivo CRISPR screening, organ regeneration, regenerative medicine

Our lab aspires to a future where we can drive the growth and repair of any organ. To achieve this, we develop and apply new technologies to understand and modulate organ regeneration directly within the living organism.

Current Projects:

We believe in working with each trainee to develop their own unique project that suits their interests, skills, and goals. Current areas of interest for potential projects include:

Bringing high-throughput functional genomics into the organism
We recently established genome-wide CRISPR screening in the mouse liver (Keys and Knouse 2022). Although genome-wide screening in the liver alone can offer novel insights into diverse phenomena, the full potential of high-throughput screening in the organism rests on expanding this technology to other organs and CRISPR applications. We are thus keen to establish efficient and stable transgene delivery and genome-scale CRISPR screening in other cell types and organs of interest in the living mouse. 

Identifying the molecular requirements for organ regeneration
The liver is the only solid organ with the capacity to regenerate itself. However, the molecular rules governing this uniquely permissive context for regeneration are unknown. We are keen to apply our in vivo genome-wide CRISPR screening platforms to identify the genes that endow the liver with its remarkable regenerative capacity as well as the genes that prohibit regeneration in other organs. By defining these genes, we will bring our goal of conferring regenerative capacity to other tissues into the realm of possibility.

Contact: knouse [at]

Location: MIT

Gabriel Kreiman - Kreiman lab

artificial intelligence, machine learning, computational neuroscience

Current Projects:

Artificial Intelligence for biomedical applications             Our Lab is interested in developing new AI algorithms for clinical applications, especially, but not restricted to, mental health disorders.

Understanding brain computations                           Our lab is interested in studying neural circuits to build better AI and developing state-of-the-art AI computational models that can help us better understand cognitive function, especially in language, memory, and vision. 

Contact: gabriel.kreiman [at] tch.harvard.edugkreiman [at]

Lab Location: Longwood

William La Cava - Cava Lab

artificial intelligence, machine learning, fairness, health equity, predictive modeling, interpretability, explainability

Current Projects:

AI approaches to improving maternal fetal monitoring: 
We're using deep learning to predict interventions during delivery, and assessing the quality and fairness of those models. 

Online fairness monitoring of prediction algorithms: 
Developing methods and code to identify and mitigate biases in heath care models. 

Investigating the fairness of large language models in health contexts: 
we're experimenting with large language models to understand what types of social biases they may encode when being used in care settings.

Contact: william.lacava [at]

Lab Location: Longwood

Laura Lewis - Imaging Brain Dynamics

neuroimaging, sleep, computational neuroscience, signal processing, machine learning, fMRI, multimodal imaging data

Current Projects:

Analyzing fast, multimodal neuroimaging data
Noninvasive tools such as fMRI and EEG allow us to measure activity in the human brain, but classically they have limited spatial and temporal resolution. We develop signal processing and computational approaches to discover new information in human neuroimaging data. For example, we use signal processing strategies to identify fast information in high temporal resolution fMRI data, and develop machine learning and analysis strategies for integrating EEG and fMRI dynamics.

Fluid dynamics of the human brain
We develop new MRI methods to measure cerebrospinal fluid flow and vascular physiology in the human brain, to understand the flow of cerebrospinal fluid and its relevance for brain waste transport.

Identifying neural circuits that control sleep
We are using novel neuroimaging techniques to identify the deep-brain neural circuits that control sleep in humans. We develop analysis methods to allow us to measure new aspects of neural circuits with ultra-high field fMRI, and apply these to identify brain systems regulating sleep.

Sleep and brain- and body-wide physiology
Sleep transforms the basic physiological processes of the brain and body. We are using multimodal neuroimaging to understand how sleep drives waves of fluid flow over the brain, and how sleep modulates body-wide physiology, such as changes in blood vessels, blood pressure, breathing, and inflammation. 

The sleeping brain in healthy aging and in Alzheimer’s disease
Healthy sleep enhances cognition, and sleep disruption is linked to serious neurological disorders such as Alzheimer’s disease. We are imaging individuals at risk for Alzheimer’s disease to understand how sleep contributes to healthy aging.

Computational neuroscience of brainwide dynamics underlying natural sleep behaviors
The sleeping brain is highly active: it consolidates information and enhances learning of tasks performed during wakefulness. In natural environments (rather than structured artificial tasks), behavior is complex, and we aim to understand how sleep supports learning of complex behaviors. This project involves machine learning approaches for analysis of latent dynamics in extremely high-dimensional longitudinal electrophysiological recordings from freely behaving and sleeping mice.

Contact: ldlewis [at]

Lab Location: MIT

Tami Lieberman - Lieberman Lab

microbiome, microbiology, genomics, evolutionary biology, computational biology, dermatology, atopic dermatitis, acne

Multiple projects available relevant to key research areas, please contact for more details.

Contact: tami [at]

Lab Location: MIT


David Liu - David Liu Lab

Genome editing, laboratory evolution, in vivo delivery, chemical biology, molecular biology, genetics, novel therapeutics, genetic diseases, organic chemistry

Current Projects:

We have many available projects in genome editing technology development, therapeutic gene editing, in vivo macromolecular delivery, protein evolution, chemical biology, and the application of all of the above to develop new treatments for previously intractable diseases.

Contact: ebotelho [at]

Lab Location: Broad Institute

Bill Lotter - Lotter Lab

AI, medical imaging, computer vision

Current Projects:

Predictive & prognostic AI for oncology

Clinically-aligned explainability of AI algorithms

Optimizing the clinical integration of AI

Contact: lotterb [at]

Lab Location: Longwood

Michael Lu - MGH Cardiovascular Imaging Research Center

AI, machine learning, coronary CT angiography, cardiology, radiology

Current Projects:

Deep learning to estimate cardiovascular aging from chest CT
This funded project's goal is to develop a deep learning model to estimate “cardiovascular age” or the risk of a future heart attack or stroke based on a chest CT. Students will use large databases comprising over 30,000 individuals and will have access to in-house computational resources to develop and test models.

Clinical trial of deep learning to identify high-risk smokers for lung cancer screening CT
This funded clinical trial will test whether a deep learning tool ( that automates identification of high risk smokers based on their chest x-ray images can improve lung cancer screening participation. 

Deep learning to uncover the effect of somatic mutations on cardiovascular disease risk
The goal of this project is to identify somatic mutations and affected biological pathways that lead to cardiovascular disease risk using UK Biobank sequencing data from over 400k participants and new interpretable deep learning technology. Responsibilities will include developing the deep learning model, and studying the output to understand genes/biological functions captured by the model.

Use confounder-free pretraining approaches to develop deep learning models to estimate disease risk
We have previously developed deep learning models to estimate cardiovascular disease and lung cancer risk from chest x-rays. The purpose of this project is to develop models that are independent of established risk factors (age, sex, smoking, etc.) using a new technique called “confounder-free pretraining”. We will then test whether these models have greater added value to existing markers of disease risk.

Contact: mlu [at] | Vineet Raghu, PhD vraghu [at]

Lab Location: MGH

Maimuna Majumder - Majumder Lab

infectious diseases, pandemic preparedness, health misinformation, artificial intelligence, machine learning, natural language processing, large language models, epidemic modeling, health policy evaluation, Bayesian inference, complex contagion, network s

Multiple Projects relevant to these Keywords

Contact: maimuna.majumder [at]

Lab Location: Landmark Center

Leonid Mirny - Mirny Lab

Genomics, Genome in 3D, Biophysical models, Hi-C data, AI, Development

Current Projects:

Several projects on chromosome organization and dynamics, modeling of enhancer-promoter interactions, and epigenetic memory are available. Requirements: proficiency in programming, experience in bioinformatic data analysis, understanding stochastic modeling.

Contact: leonid [at] mit.edupkatrina [at]

Lab Location: MIT

Sahar Nissim - Nissim Lab

pancreatic cancer, cell identity, single cell and spatial transcriptomics and epigenetics, cancer interception

Pancreatic cancer has notoriously ineffective treatment options and will take the lives of over 50,000 individuals in the U.S. this year. We have a vibrant team applying innovative bench and computational approaches to pioneer a cancer “interception” strategy: a way to restrain or revert pancreas precursor lesions before they have a chance to become cancer.

Current Projects:

Epigenetic determinants of pancreas cell identity: 
The identity of acinar cells, the cell of origin of pancreatic cancer, is maintained by a gene regulatory network of transcription factors and epigenetic states. How are these regulators of normal cell identity disrupted by stressors that promote cancer (inflammation, obesity, and an oncogenic Kras mutation)? And, can we target these regulators to stabilize normal cell identity for cancer interception? Interested students will have access to a complement of mouse models, human pancreas cultures, new transcriptomic and epigenomic pipelines developed in the lab, and functional tools to help answer these questions.

“Amnesia” of prior inflammatory stress:
Cells that recover from inflammation are thought to harbor epigenetic scars that distinguish them from naïve cells. These scars may explain why pancreatitis is a risk factor for pancreatic cancer. During pancreatitis, acinar cells transiently undergo metaplasia but then completely recover histologically. Though they appear normal, these recovered acinar cells have durable epigenetic marks of metaplasia that may facilitate cancer initiation. Interested students can (i) define these epigenetic marks and (ii) determine whether we can pharmacologically reverse these epigenetic marks to achieve “amnesia” of pancreatitis as an interception strategy for cancer. 

Reprogramming the immune microenvironment in pancreas cancer formation:
Pancreatic cancer is refractory to immunotherapy due to active evasion mechanisms. In this project, students will study how stressors that promote pancreatic cancer (including obesity, inflammation, and an oncogenic Kras mutation) reprogram the pancreas microenvironment to actively suppress immune surveillance.

CRISPR somatic genome engineering in mouse pancreas:
Single cell transcriptomic and epigenomic studies identify candidate pathways that regulate pancreas biology and disease. However, tools to functionally validate these pathways in the pancreas are limited. In this project, students will help establish in vivo CRISPR-mediated genome engineering in the mouse pancreas that will be critical to validate strategies for pancreatic cancer interception and treatment.

Understanding metabolic dysfunction in the pancreas:
The pancreas is composed of histologically distinct exocrine and endocrine compartments. Individuals diagnosed with pancreatic cancer often initially present with metabolic abnormalities including new-onset diabetes and severe weight loss, suggesting that an incipient cancer dysregulates adjacent endocrine pancreas cells. In this project, students will harness single cell and spatial transcriptomic tools to understand mechanisms of crosstalk between the exocrine and endocrine pancreas in the context of obesity, pancreatitis, and cancer.

Contact: snissim [at]

Lab Location: Longwood


Darren Orbach - Cerebrovascular Surgery and Interventions Center

Neurosurgery, MRI, segmentation, quantitative physiology, fetal imaging

The Cerebrovascular Surgery and Interventions Center is a multidisciplinary center treating rare pediatric brain vessel diseases. Research focuses on using quantitative imaging techniques to improve prognostication and to monitor treatment progress. With a team of clinicians dedicated to improving treatment strategy, projects are focused at the intersection of advanced quantitative imaging and clinical utility.

Current Projects:

Quantitative cerebral flow metrics to guide cerebrovascular surgery and endovascular interventions
Quantitative flow imaging informs us of discrete metrics of responses to endovascular and open surgical treatments of the brain vessel diseases—this can allow us to be more precise in our use of treatment strategies, minimizing the risk while not compromising the effectiveness of the treatment. These metrics also help us develop tools to predict which patients need treatment and when they should have different types of treatments. This work extends to pioneering in utero interventions to treat vein of Galen malformation.

Advanced quantitative flow MRI
We have begun acquiring 4D Flow MRI on many of our patients. This is possible due to highly accelerated acquisition strategies and trade offs in terms of temporal and spatial resolution. We are working to use machine learning techniques to reconstruct super resolution data to improve quantification of pressure and flow in small vessels. We plan to compare these reconstructions with gold standard invasive measurements.

Physiological MRI for prognosis and treatment planning pediatric moyamoya disease
There are surgical treatments that reduce stroke risk in children with moyamoya disease, but knowing when to intervene and who will most benefit, especially in asymptomatic cases, is an open question. We are exploring the uses of MRI-based cerebrovascular reactivity mapping and perfusion imaging to better predict outcomes and treatment responses in children with moyamoya disease.

Interaction between genetics and blood flow
AVMs, aneurysms, vein of Galen malformations, and moyamoya are diseases of the blood vessels that affect children. They are often rooted in the blueprints that guide development of the vessels and how the blood vessels respond to blood flow. We are studying this interaction at two distinct and complementary levels. At the laboratory bench, we study the surface molecules on the blood vessel cells that detect and communicate to the rest of the cell about normal and abnormal flow, to change the programming of the cell function. This is complemented by the quantitative imaging techniques described above that measure the precise flow in each involved vessel. Connecting the flow measurements from actual patients with genetic mutations in their diseases may identify the way that the disease worsens over time or the way it can respond to surgical treatments.

Contact: darren.orbach [at]

Lab Location: Longwood - Boston Children's Hospital

David Page - Page Lab

sex differences in health and disease, including heart disease, autism, autoimmune disease, and cancer; X and Y chromosomes; X inactivation

Rethinking the genetics of the human X chromosome and its role in sex biases in diseases like autism and autoimmunity. Could the X chromosome hold the key to the "female protective effect" in autism?

Current Projects:

Computational and biochemical analyses of sex differences in metabolism in the heart, immune cells, adipose, and across the body.

Computational, genomic, and epigenomic studies of human preimplantation embryos, with the aim of understanding the beginnings of X chromosome inactivation and sex differences prior to the action of sex hormones.

Computational studies of the impact of gender-affirming therapies on gene expression in peripheral blood mononuclear cells.

Contact: dcpage [at] | Susan Tocio, page_admin [at]

Lab Location: Whitehead Institute/MIT

Peter Park - Computational Genomics

bioinformatics, large-scale computation, cancer, neuroscience, whole-genome sequencing, single cell sequencing

Current Projects:

Somatic mutations in non-cancer cells
How to mutations arise in the first place?  How can we detect those rare mutations in genome sequencing data?  Can we find mutations from single cell sequencing data?  Can we use somatic mutations as barcodes to understand developmental processes?  

Development of matrix algorithms
Can we use matrix factorization-based approaches to identify distinct mutational processes?  Can we use our understanding of mutational processes to improve therapy selection for cancer patients?

Contact: peter_park [at]

Lab Location: Longwood

John Pezaris - Visual Prosthesis Laboratory

artificial sight, lgn, lateral geniculate nucleus, visual prosthesis, phosphenes

Current Projects:

Optokinetic nystagmus in a simulation of artificial vision
Sighted human subjects are used to measure the learning rate of the OKN response in a simulation of artificial vision. Work in concert with PI and lab technician.  A sufficiently motivated student will be able to lead this project and work on additional, similar projects afterward. Students will be required to obtain clearance to work with human subjects.

Color / size / duration of phosphenes in a non-human primate model of artificial vision
Work in concert with PI, post-doc and lab technician.  Students would take one portion of the larger project. Students will be required to obtain clearance to work with non-human primate subjects.

Understanding the trajectory of fine-wire brush electrodes during implantation
Students will learn to construct fine-wire brush electrodes and photograph their penetration into agar in order to understand how to control electrode splay during insertion into brain tissue. These electrodes will be used in a visual prosthesis.

Contact: pezaris.john [at]

Lab Location: MGH Main Campus

Jon Polimeni - High-Resolution and Ultra-High-Field Functional Imaging Laboratory

brain imaging, high-resolution functional MRI, ultra-high field MRI, human neuroscience, MRI technology development, laminar fMRI, biophysical modeling

Current Projects:

In vivo neuroimaging of the human brain tissue’s mechanical response to neural activation
This ongoing project, funded by two NIH grants, seeks to develop and apply new tools to measure the mechanical response of the cerebral cortex to focal neural activation elicited e.g. through visual stimulation. We are developing new approaches to measuring changes in tissue and surrounding cerebral spinal fluid expansion and compression driven by either neural or vascular responses. These measurements will help answer fundamental questions about brain physiology needed for understanding the brain’s glymphatic clearance system as well as advanced functional MRI methods.

Contact: jonp [at] mit.edueperelgut [at]

Lab Location: Martinos Center

Max Prigozhin - Prigozhin Group

Cell signaling, GPCR signaling, cryo-vitrification, electron microscopy, super-resolution imaging

Current Projects:

Understanding the spatiotemporal logic of GPCR signaling
Throughout their lives, biological cells integrate millions of dynamic, sparse, and even conflicting environmental cues to make key decisions: proliferate or differentiate, migrate or stay put, live or die. To accomplish these tasks, cells use molecular information processing modules. We focus on visualizing the spatial organization and temporal dynamics of these molecular signal processing modules.

Contact: maxim_prigozhin [at]

Location: Harvard

Maggie Qi - QI Research Group

biomechanics, soft matter, biological microfluidics

Current Projects:

Retina-on-a-chip for ophthalmology research

Bomechanical modeling for drug carrier design

Contact: qmqi [at]

Lab Location: MIT

Ron Raines - Raines Lab

chemical biology, protein structure–function, cancer, fibrosis

Current Projects:

Chemical Biology in the Extracellular Matrix
Collagen is the most abundant protein in humans and the major component of the extracellular matrix. We revealed the fundamental bases for the conformational stability of the collagen triple helix. Using that knowledge, we developed a collagen-mimetic peptide that anneals tightly and specifically to damaged collagen in fibrotic tissue and the tumor microenvironment. Now, we seek to exploit our peptidic “pylon” to anchor PET/MR probes and target drug delivery in preclinical contexts.

Ribonucleases as Cancer Chemotherapeutic Agents
By catalyzing the degradation of RNA, ribonucleases act at the crossroads of transcription and translation. We enabled a human secretory ribonuclease to evade an endogenous inhibitor protein and thereby endowed the enzyme with toxicity for cancer cells. That ribonuclease has been used to treat solid tumors in the clinic. We now seek to enhance its biomedical attributes and further elaborate on the biological roles of secretory ribonucleases.

Delivery of Therapeutic Proteins into Human Cells
Biologic drugs are restricted to extracellular targets, leaving ¾ of disease-relevant proteins undruggable. To overcome this limitation, we developed cationic and boronic acid-based pendants to transport proteins into cells. Recently, we discovered how to “mask” protein carboxyl groups by esterification with tuned diazo compounds. These protein “prodrugs” can enter the cytosol, where human esterases hydrolyze the nascent esters. We are especially interested in delivering PTEN, which is a phosphatase that is often deficient in human cancer cells.

Contact: rtraines [at]

Lab Location: MIT

Pranav Rajpurkar - Rajpurkar Lab

Medical AI; Medical Image Interpretation

Current Projects:

Development of Generalist Medical AI for Diagnosis
In this project, students will work on developing a Generalist Medical AI system that is capable of reasoning through various medical tasks similar to a human doctor. By incorporating multiple data modalities, such as images, sensors, and natural language, the project aims to provide a comprehensive AI system that can analyze and diagnose medical conditions across different fields of medicine.

Self-Supervised Learning for Disease Detection
This project focuses on furthering the development of self-supervised and pre-trained adaptable medical models for detecting diseases in chest X-rays without the need for explicit labels. Building on the group's prior success, students will explore new techniques and models that can expand the capability of these foundation models, potentially extending to other medical domains like electrocardiograms and CT scans.

AI Copilot for Radiology Report Generation
Students involved in this project will pioneer the "copilot" approach to radiology report generation. Leveraging generative AI models, the project aims to create AI systems that provide initial drafts of radiology reports that can be further edited and refined by clinicians. The project will not only focus on the technical aspects but also investigate the behavioral implications of providing AI assistance to clinicians and explore how to ensure trustworthiness and explainability in the system.

Contact: pranav_rajpurkar [at]

Lab Location: Longwood

Jian Ren - The Ren Lab

brain mapping; Alzheimer’s; bioimaging; optics; microscopy; signal processing; performance limit of imaging systems; tissue engineering; nanomedicine; graph; topology; image formation, analysis, and informatics; 3D visualization; novel medical devices

Current Projects:

Optical: High-throughput volumetric imaging

Biochemical: Long-lasting nano-scale proteomic contrast synthesis

Computational: Cross-scale cross-modality image validation, graph analysis, and topological abstraction

Translational: multimodal systems and miniaturized device

Contact: jren [at]

Lab Location: Charlestown

Elizabeth Rossin - Ocular Genomics Institute

Genetics, genomics, retina, proteomics

Current Projects:

Genome wide association studies and exome sequencing in complex retinal disease. 
We are in the process of recruiting and genotyping patients at MEE to study various retinal phenotypes including central serous chorioretinopathy, epiretinal membrane, macular degeneration and proliferative vitreoretinopathy. We also access various biobanks to analyze these phenotypes.  We run follow up studies on patient sera and single-cell sequencing on patient-derived surgical specimens.

Structure based network analysis (SBNA). 
SBNA is a pipeline in python and R we built to analyze mutations in the context of protein structure. We have found this works well in predicting which genetic variants will contribute to retinal disease. Ongoing projects include applying this pipeline more broadly across the genome and running directed followup experiments.

Contact: elizabeth_rossin [at]

Lab Location: Massachusetts Eye and Ear

Seward Rutkove - Seward Rutkove Lab for Neuromuscular Health and Disease

Neuromuscular, gravity, muscle, biomarkers, neurophysiology, micro- and fractional-graviity

Multiple projects available relevant to key research areas, please contact for more details.

Contact: srutkove [at] bidmc.harvard.edusverga [at]

Location: Longwood

Pardis Sabeti - Sabeti Lab

Infectious Disease; Computational Biology; Genomics; Viruses; Sequencing

Contact: pardis [at]

Lab Location: Broad Institute of MIT and Harvard

David Salat - Brain Aging and Dementia (BAnD) Lab

Aging, Alzheimer's Disease, Brain Mapping, Cardiovascular Disease, Clinical, Data Science, Diffusion MRI, EEG, fMRI, FreeSurfer, Functional Magnetic Resonance Imaging, Machine Learning, PET, Positron Emission Tomography, TBI, Traumatic Brain Injury

Current Projects:

Machine learning diagnosis of Alzheimer's disease from brain imaging data
This project aims to develop novel procedures for the identification of Alzheimer's disease brain pathology early in the course of the disease.

Examination of factors related to cognitive resilience in late age using brain imaging 
This project aims to determine neural factors that contribute to optimal cognitive function in older adults very late in life when most of their peers exhibit a decline in function.

Examination of mechanisms of brain aging and neurodegeneration
This project aims to determine genetic, lifestyle, and medical factors that contribute to healthy and degenerative brain aging.

Contact: dsalat [at] | Katherine Nadine Maina KNMAINA [at]>

Lab Location: Charlestown

Sol Schulman - Schulman Lab

Blood coagulation, bleeding, thrombosis, functional genetics, cell biology, biochemistry

Current Projects:

Functional Genetics of Tissue Factor in Bleeding and Thrombotic Risk
This project integrates functional genetics with human population data to identify new sources of tissue factor-dependent bleeding and thrombotic risk.

Cancer-Associated Thrombosis
This project uses functional genetics, cell biology, and rodent models to explore the molecular basis for cancer-associated thrombosis.

Role of SARS-CoV-2 ORF3a in COVID-19-Associated Coagulopathy
This project aims to define the virus-intrinsic mechanisms by which SARS-CoV-2 leads to pathologic blood coagulation.

Contact: sschulm1 [at]

Location: Longwood

Ayellet Segrè - Segrè Lab

Genetics of complex eye diseases, computational genomics, expression and splicing QTLs and single cell RNA-seq of eye tissues, interpretation of noncoding variation, whole exome sequencing, GWAS, genotype-phenotype biobank analyses, polygenic risk scores,

In the Segre lab we are interested in developing and applying computational and statistical methods that integrate large-scale genetic association and sequencing data with functional genomics data to identify causal regulatory mechanisms, genes, pathways, and cell types that affect complex retina-related diseases, such as primary open angle glaucoma (POAG) and age-related macular degeneration (AMD). We collaborate with clinician scientists in the Ocular Genomics Institute at Mass Eye and Ear.

Current Projects:

Integrating polygenic risk scores and single cell expression to uncover disease mechanisms and subtypes 
We are working on developing methods for building and training cell-type specific polygenic risk scores in large-scale genotype-phenotype biobanks using GWAS meta-analyses and single cell transcriptomics data. We will apply this approach to common retina-related diseases, such as glaucoma, using single-nucleus RNA-seq data from disease-relevant anterior and posterior eye tissues. Association with clinical traits and matrix factorization approaches will be used to identify disease mechanisms and subtypes.

Genetic regulation of gene expression and splicing in ocular tissues and cell types and role in disease
We will leverage our experience in the Genotype-Tissue Expression (GTEx) project to identify genetic regulation of gene expression (eQTLs) and alternative splicing (sQTLs) in anterior and posterior eye tissues that contribute to the pathogenesis of glaucoma, using linear regression models of RNA-sequencing and whole genome sequencing data. We are also working on methods to detect genetic regulation at the single cell level in eye tissues. We will integrate this genetic regulation information with glaucoma GWAS loci to propose underlying causal regulatory mechanisms and genes.

Pharmacogenetic studies of drug treatment response or adverse effects
We are working on several pharmacogenomic projects in collaboration with Dr. Lucia Sobrin at Mass Eye and Ear aimed at identifying common and rare variants associated with response to drug treatment in diabetic retinopathy patients or adverse effects of steroid treatment in the eye. Genomic analyses include genome-wide association studies (GWAS), enrichment of rare deleterious mutations in genes (gene burden tests) in patients with poor versus good drug response using whole exome sequencing, and integrative functional genomic analyses of the genetic discoveries. 

Cell-cell interactions in the retina and optic nerve head and effect on glaucoma
Using a computational method we developed (ECLIPSER) that integrates GWAS loci of complex diseases with single cell expression and e/sQTLs, we found that dysregulation of genes in macroglial cells may play an important role in glaucoma development, which is characterized by retinal ganglion cell (RGC) death. We are interested in using receptor-ligand and covariation analyses of single cell RNA-seq data of human retina, and integration with genetic associations with glaucoma, to identify molecular interactions between neuronal support cells, such as astrocytes, and RGCs, that may be important contributors to RGC sensitivity. This research direction may be further explored through different mechanistic models.

Contact: ayellet_segre [at]

Lab Location: Mass Eye and Ear, 243 Charles Street, Boston

Shiladitya Sengupta - Center for Engineered Therapeutics

Nanoscience, Cancer, Immunology, Drug Development

Current Project:

A nanoscale insight into how cancer and immune cells interact and using that information to engineer next generation therapies.

Contact: shiladit [at]

Lab Location: Longwood and 65 Landsdowne street

Alex Shalek - Shalek Lab

We combine genomics, chemical biology, and nanotechnology to construct accessible and widely-useful cross-disciplinary platforms that enable us and others to profile and control cells and their interactions. By applying these approaches with partners arou

Current Projects:

The Shalek Lab develops and applies broadly applicable experimental and computational platforms to understand and engineer immune responses in tissues. We employ a comprehensive, five-step approach, building innovative methodologies and leveraging them with partners around the world to facilitate deeper, more mechanistic inquiry into how cells drive tissue-level behaviors across the spectrum of human health and disease.

Contact: shalek [at]

Lab Location: MIT

Richard Sherwood - Sherwood Lab

CRISPR, complex genetic disease, chromatin, base editing, cardiovascular disease

Current Projects:

Our lab is a highly interdisciplinary and collaborative environment that combines CRISPR-Cas9 genome editing and genomic screening approaches with cutting edge machine learning and computational genetics approaches to understand how genomic variants contribute to complex human disease and to develop genetic treatments. We have a particular focus on using CRISPR base editing and prime editing screening and biobank genetics datasets to understand and develop treatments for cardiovascular disease risk factors.

Contact: rsherwood [at]

Location: Longwood

Chris Smillie - Smillie Lab

host-microbiome interactions, single-cell RNA-seq, spatial transcriptomics

Current Projects:

Single-cell genomics of the human microbiome
We are working on the development of new methods for single-cell transcriptomics of bacteria. We are currently applying these methods to the human gut microbiome. There is a big opportunity to develop new computational methods for these datasets and to study bacterial heterogeneity on the human body.

Spatial transcriptomics of the human intestine
We are working on the application of spatial transcriptomics to intestinal tissue resections from IBD patients. We are developing new computational methods to discover interactions between cell types. Our goal is to understand what are the tissue drivers of inflammation.

Discovering host-microbiome interactions in large datasets
Gut bacteria have evolved exquisite mechanisms for manipulating our immune systems and the functioning of diverse cell types (e.g. epithelial cells and even neurons). We are interested in discovering the bacterial strains, genes, and molecules that drive these effects. We are developing unique ways of doing this that leverage large datasets.   

Contact: csmillie [at] mgh.harvard.educssmillie [at]

Lab Location: MGH

Jason Stockmann - MR Physics and Instrumentation Group

MRI hardware, RF coils, new spatial encoding approaches, neuromodulation

Current Projects:

I am broadly interested in new hardware and software for improving the resolution, sensitivity, and acquisition speed of MRI, as well as multi-modal approaches such as functional MRI with concurrent transcranial magnetic stimulation (TMS) for causal mapping of brain circuits. We are beginning a new BRAIN Initiative project to use multi-channel TMS coils to perform local spatial and diffusion encoding. The aim is to achieve very strong local diffusion encoding (b-values) in the cortical gray matter to improve our ability to study brain tissue microstructure at spatial scales much smaller than the imaging voxel.  The project involves electronics, mechanical design, systems integration, image reconstruction, and pulse sequence Bloch simulation. There are also opportunities to learn about brain stimulation in collaboration with Dr. Aapo Nummenmaa's TMS lab.

Contact: jstockmann [at]

Lab Location: Charlestown Navy Yard

Joelle Straehla - Straehla Lab

drug delivery, blood-brain barrier, pediatric brain tumor, genomic determinants of nanoparticle delivery

Any interested students should feel welcome to reach out to the PI about their ideas for short- or long-term projects. For example, we have interests ranging from basic (genetic screens to elucidate mechanisms of nanoparticle trafficking) to preclinical (investigating nanoparticle therapeutics in cancer models) to clinical (evaluating the blood-tumor barrier in pediatric brain tumor patient samples). There are many opportunities for collaborative projects working with clinicians and researchers in pediatric neuro-oncology.

Contact: jstraehl [at]

Lab Location: Koch Institute at MIT

Michael S. Strano - Strano Research Group

bladder cancer, cell manufacturing, biosensing, drug design, diabetes, biomedical imaging, biomedical computation

Current Projects:

3D Chemical Tomography for the Diagnosis and Treatment of Bladder Cancer 
This project advances a novel biochemical imaging platform under development in the Strano laboratory at MIT for the detection of cancerous and pre-cancerous tumors important for the diagnosis and treatment of bladder cancer.  Bladder cancer currently affects 1.6 million people, and is one of the most expensive diseases in medicine because of its extraordinarily high rate of recurrence.  Research will uncover and develop relevant cancer biomarkers, and examine cellular and tissue level chemical imaging of tumor efflux in real time as an aid in diagnosis and treatment. This project is in collaboration with Dr. Mark Preston, Associate Surgeon in Urology and Dr. Daniel Wollin, Urologic Surgeon at the Brigham and Women's Hospital at Harvard Medical. 

Glucose Responsive Glucagon Drug Design and Analysis 
Diabetes is a disorder that alters the body’s natural glucoregulatory operation. It is known to involve complex independence of key signaling molecules such as glucose, insulin, and glucagon.   This project leverages a novel computational modeling framework developed by the Strano laboratory at MIT that performs in silico simulations of the glucoregulatory system in humans and animal models.  Collaborators at the University of Notre Dame, University and Toronto and Indiana University are working with our MIT team to design a next generation of diabetes therapeutics.  This project, funded by the NIH and the Helmsley Foundation, will leverage experimental and clinical data to guide drug design in this biomedically important area.

Nanosensor Chemical Cytometry for the Measurement of Cellular Chemical Signals in Therapeutics Manufacturing
There is a need for detection platforms to the study intracellular and pericellular biochemical signals from living cells and microbes that performs rapid, non-destructive and label-free measurements. The Strano group at MIT has recently developed Nanosensor Chemical Cytometry (NCC) that is able to probe biochemical heterogeneities from cellular populations by employing a combination of microfluidics with nanosensor arrays that can measure chemical efflux from each cell. One potential application of this technology is to monitor the quality of cellular therapeutics in the process of manufacturing. This thesis will involve sensor engineering, platform development, cellular studies and computational analysis.

Contact: strano [at] mit.edusrgoffice [at]

Lab Location: Building 66, 5th floor, MIT Campus

Atchar Sudhyadhom - Atchar Lab

medical physics, radiation therapy, MRI, proton therapy, radiation chemistry

Current Projects:

Real-time MRI of Radiation Chemistry in Patients
Atchar Lab is the first group to show images of radiation effects in real-time. The long-term goal of this project is to see the actual damage that radiation creates in patients using a clinical MR-linac machine, the only such machine in the state of Massachusetts. The research involves using an MR-linac, acquiring MR images, image reconstruction/post processing using conventional and machine learning methods, and simulation of radiation interactions.

MR Guided Proton Therapy
This project would involve developing methods to pinpoint proton therapy beam treatments in the body using only MRI scans of a patient. The research involves using a proton therapy machine, acquiring MR images, post processing using conventional and machine learning methods.

MR Functional Adaptive RT
The current state of the art in radiation therapy involves daily adaptation of patient treatments based off anatomic changes. The long-term goal is to acquire and adapt patient treatments to biological/functional changes rather than just anatomic information. This research involves developing in vivo clinically-feasible T1 mapping, hypoxia, and diffusion imaging and associated image processing methods by conventional and machine learning methods.

Contact: Atchar_Sudhyadhom [at] | Noah Warner nswarner [at]

Lab Location: Longwood

David Ting - Ting Lab

repetitive elements, pancreatic cancer, metastasis

Current Projects:

Spatial transcriptomic profiling of cancer: 
Using spatial molecular imaging (Nanostring CosMx) we are building single cell maps of a variety of cancers including pancreatic, liver, colon, lung, and sarcoma to understand cell-cell interactions.

Unlocking the cancer repeatome:
Cancers aberrantly express non-coding repeat RNAs that behave like viral elements in our genome.  We are using a combination of small molecule and genetic strategies to understand the role of therapeutically targeting these repeat elements in cancer. 

Contact: dting1 [at]

Lab Location: Charlestown 

Mehmet Toner - Center for Engineering in Medicine & Surgery

BioMEMS and Nanoscale Engineering; Biopreservation Burns, Trauma and Wound Healing; Cell and Genetic Engineering; Cell Migration in Disease; Cell Sorting and Cancer Diagnosis; Global Health; Neuroscience and Behavior Organ Reengineering; Tissue Engineerin

The Center for Engineering in Medicine & Surgery laboratories is a multi-disciplinary collaborative environment with teams of engineers, scientists and clinicians. We are interested in recruiting several students in the following areas

Current Projects:

The bioengineering and clinical applications of circulating tumor cell chip especially for early diagnosis and personalized oncology funded by multiple NIH and various Foundation grants (Edd et al., iScience 2022). The exact nature of the project depends on the student’s interest and can vary from technology development to fundamental biological investigation as well as clinical translation. 

The fundamental and applications of achieving ‘suspended animation’ in living systems (from cells to organs) funded by a large NSF Engineering Research Center grant as well as multiple NIH and DoD grants (Tessier et al. Nature Comm 2022)

Contact: mtoner [at]

Lab Location: Charlestown

Zuzana Tothova - Tothova Lab

Epigenetics, leukemia, MDS, clonal hematopoiesis, repetitive elements, splicing

We are a basic and translational research laboratory that focuses on mechanisms of blood cancer development and translate our findings to therapeutic strategies. We use a variety of models including cell lines, CRISPR engineered mouse transplant models, transgenic and patient derived xenograft models and primary patient samples. We have been interested in dissecting and targeting mechanisms by which chromatin complexes, including the Cohesin complex, mediate clonal dominance and disease progression in CHIP and MDS.

Current Projects:

Role of transposable elements during the development of blood cancers and adaptation to inflammation.

R loops as regulators of clonal dominance in Cohesin-mutant MDS.

Dissecting the mechanisms of dependency of Cohesin-mutant myeloid malignancies on splicing

Contact: zuzana_tothova [at]

Lab Location: Tothova Lab

Korkut Uygun - Organ Reengineering Laboratory

Supercooling; Mitotherapy; Organ Genetic Engineering; Transplantation; Machine Perfusion

Current Projects:

End stage organ failure is the number one cause of death in the US with a total mortality exceeding that of cancer. The ability to replace organs through transplantation on demand has potential to save or improve millions of lives each year globally. Although part of the problem is a limited supply of donor organs, the key issue is the limited time organs can survive outside the body. The clinical gold standard is storage in a bag of ice, a technology that was invented half a century ago and allows only hours of storage time. Our lab aims to develop the next generation technologies to abolish the waiting list for organ transplantation and allow global sharing of organs as well as tissue engineered products. Current areas of focus include i) mitotherapy (i.e. mitochondria transplantation); ii) ex-vivo genetic engineering for immunomodulation; iii) supercooled organ preservation; iv) novel biomarker development (Raman spectroscopy, thermal imaging, theranostics via genetic engineering); v) AI use for equitable distribution of donor organs globally, among others. The lab consists of over 20 researchers with active studies in liver, kidney, face and hand transplantation in a very vertically integrated fashion spanning organelle and cell isolation to clinical trials in transplantation.

Within this broad scope of lab expertise, the projects are developed jointly. The mentorship team often includes multiple faculty with a broad range of expertise in systems engineering, cryobiology and clinical transplantation as well as others depending on the scope of the thesis project.

Contact: kuygun [at]

Location: MGH Main Campus

Ben Vakoc - The Center for Biomedical OCT Research

optical imaging, optical coherence tomography, intraoperative imaging

Current Projects:

We have several open positions in the design, construction, and clinical translation of novel intraoperative imaging technologies. Project areas include the design and fabrication of integrated photonic light sources and interferometric systems, the co-design of machine learning and optical imaging hardware, and the clinical validation of these instruments in ophthalmology, head and neck surgery, and neurosurgery.

Contact: bvakoc [at]

Lab Location: MGH (main campus)

Susanne van Veluw - Translational CAA Research Lab

cerebral amyloid angiopathy, small vessel disease, MRI, neuropathology, two-photon microscopy

Current Projects:

The role of vasomotion in perivascular brain clearance

The role of inflammation in vascular remodeling and hemorrhage

Contact: svanveluw [at]

Lab Location: MGH main campus & Charlestown

Srinivas Viswanathan - Viswanathan Lab

genomics, functional genetics, integrative genomics, cancer genetics

Our lab uses cutting-edge genomic and genome-scale functional genetic technologies to dissect the molecular underpinnings and vulnerabilities of cancer, with a focus on genitourinary cancers (particularly cancers of the prostate and kidney).  Several exciting projects involving integrative genomics are currently available. Most projects have opportunities for both wet-lab and dry-lab (bioinformatics) exposure.

Current Projects:

Specific areas of research include the following: 

Use of functional genetic (CRISPR) screening and large-scale mass spectrometry to identify new drug targets in prostate cancer. 

Genome-scale genetic and drug-screening of kidney cancer cell line and organoid models in order to identify new therapies for various subtypes of cancer

Molecular biology and biochemistry studies to understand the basic mechanisms by which oncogenes in prostate and kidney cancers drive these diseases, with a particular focus on core transcriptional programs driven by fusion oncogenes. 

Analysis of whole genome and transcriptome (bulk and single-cell) sequencing data from patients with prostate and kidney cancers.  

Contact: srinivas.viswanathan [at]

Lab Location: Longwood

David Walt - Walt Laboratory for Advanced Diagnostics

diagnostics, cancer, neurodegenerative disease, infectious disease, biosensors, single molecules, extracellular vesicles

Current Projects:

We develop new technologies that address unmet needs in diagnostics.  Our projects are centered around biomarker discovery, ultrasensitive protein detection, and extracellular vesicles. We aim to develop new diagnostics technologies for neurodegenerative diseases (Alzheimer's, Parkinson's), multiple cancers (breast, ovarian, pancreatic), and infectious diseases (HIV, TB, long COVID)

Contact: dwalt [at] | Ceara Buzzell: cbuzzell [at]

Location: Longwood

Brandon Westover - CDAC

machine learning, AI, electroencephalography, EEG, neurology

Current Project:

We work on automating and the interpretation of clinical neurophysiology diagnostic tests, including EEG done to evaluate suspected epilepsy, EEG done in the ICU setting for prognosis and detection of harmful brain activity, and polysomnography done to evaluate sleep disorders. We also work to extract hidden information about health and disease from EEG signals. Finally, the lab does large-scale EHR phenotyping and NLP work to support the EEG studies. 

Contact: bwestove [at]

Lab Location: BIDMC

Ona Wu - Clinical Computational Neuroimaging Lab

Quantitative Imaging Biomarkers, Machine Learning, Deep Learning, Stroke, Cardiac Arrest, Traumatic Brain Injury, Disorders of Consciousness, MRI, CT

Current Projects:

Automated acute ischemic stroke infarct segmentation
Refine/develop machine learning algorithms to segment/predict acute stroke lesions using multiple modalities on either CT or MRI. 

Automated white matter lesion segmentation
Refine/develop machine learning algorithms to segment white matter lesions on FLAIR MRI. 

Brain connectivity
Investigate structural and functional connectivity changes after brain injury

Contact: ona.wu [at]

Lab Location: Charlestown Navy Yard

Ramnik Xavier - Xavier Lab

autoimmunity, mechanisms and chemical biology of genetic variants, genotype-to-phenotype maps, functions of gut microbes and their metabolites, intersection of microbiome chemistry and host genetics, antigen discovery, mucosal immunity, tissue homeostasis

Current Projects:

The Xavier Lab, spanning the Department of Molecular Biology at Massachusetts General Hospital and the Broad Institute, focuses on systematic characterization of genetic variants to understand the regulation of barrier defense and innate and adaptive immunity; chemical biology to control cellular disease phenotypes suggested by human genetics; molecular functions of the microbiome to determine impacts on health and disease; and development of prediction algorithms to identify immunodominant antigens that drive pathogenic and homeostatic T cell responses.

Contact: xavier [at] | Lillian Blizard, lblizard [at]

Location: Massachusetts General Hospital and Broad Institute

Seok Hyun (Andy) Yun - Yun Lab

Optics, Imaging, Single cell analysis, Technology

Current Projects:

Optical barcoding technologies for single cell analysis and massively multiplexed assays

Multi dimensional single cell data acquisition and integration

Elastography for ophthalmology

Contact: syun [at]

Lab Location: Landsdowne St., Cambridge

Xin Zhou - Zhou Lab

protein and cell engineering

Current Projects:

Engineering membrane and extracellular protein degraders

Protein post-translational modification mapping and reprogramming

Designing programmable enzymes for proteome editing

Contact: xin_zhou1 [at]

Lab Location: Longwood