Postdoctoral Research Fellow

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The General Hospital Corporation

Mass General Brigham relies on a wide range of professionals, including doctors, nurses, business people, tech experts, researchers, and systems analysts to advance our mission. As a not-for-profit, we support patient care, research, teaching, and community service, striving to provide exceptional care. We believe that high-performing teams drive groundbreaking medical discoveries and invite all applicants to join us and experience what it means to be part of Mass General Brigham.

Job Summary

The salary range for this position is $70,000 to $ 71,750 annually.

The Vazquez-Garcia Lab, part of Massachusetts General Hospital, Harvard Medical School, and the Broad Institute, is seeking exceptional candidates for a postdoctoral position in our interdisciplinary team.

Our lab investigates the fundamental principles of somatic evolution and immune surveillance in cancer. We use data-driven approaches to study cellular dynamics in tumors, combining AI/ML, single-cell genomics, and cellular imaging approaches with large clinical datasets and experimental models. Our research draws on multi-modal data from basic science and clinical practice to understand how genomic adaptations confer selective advantages to tumor cells, act as biomarkers of therapeutic response and resistance, and sensitize tumors for targeted intervention.

Our ultimate goal is to impact human health and clinical care for patients, leveraging our understanding of cancer trajectories to enable biomarkers and therapeutic strategies that anticipate and overcome tumor progression.

You will join a highly collaborative and interdisciplinary group committed to tackle challenging problems in computational oncology. You will work on independent research projects within the lab, and actively collaborate with colleagues across MGH, HMS, the Broad Institute and other institutions. You will be part of a vibrant scientific community and will have access to state-of-the-art computational resources and high-throughput genomics technologies.

The main responsibilities will include but not be limited to:

● Design, train, and evaluate cutting-edge AI and statistical models using large patient datasets.

● Build robust pipelines for large-scale data processing and benchmarking across modalities.

● Collaborate closely with cancer biologists, clinicians, and other computational researchers to generate testable hypotheses and interpret findings.

● Perform exploratory research in a fast-paced setting with the potential for real impact on patients.

● Contribute to the development of high-quality, reusable, open-source software.

● Publish research in top-tier journals and present at major conferences.

● Help foster a collaborative lab environment by advising and supporting junior team members.

Qualifications

Minimum qualifications:

* Ph.D. (or near completion) in a relevant field such as Computational Biology, Computer Science, Physics, Mathematics, Statistics, or a related quantitative discipline.

* Demonstrated proficiency in Python, R and/or other scientific computing languages.

* Proven track record of productivity through peer-reviewed publications.

* Excellent written and verbal communication skills.

* Ability to work independently and as part of a collaborative team.

* Strong organizational skills and attention to detail.

Preferred experience:

* Proven experience working with high-dimensional, multi-modal omics data and clinical data.

* Strong background in advanced statistical modeling and/or modern machine learning approaches (e.g. transformers, foundation models, generative modeling, interpretable AI).

* Knowledge of cancer biology, immunology, or molecular biology.

* Familiarity with cloud computing and workflow management (e.g., Nextflow, Snakemake).

* Experience with version control and software engineering practices.

* Interest in contributing to open-source bioinformatics software.

To apply , please submit a CV, representative publications or preprints, a statement of prior research and future interests, and contact information for three references to Ignacio Vazquez-Garcia, PhD at ivazquez-garciavard.edu.

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