Metro New York & Southern Connecticut

The people of Memorial Sloan Kettering Cancer Center (MSK) are united by a singular mission: ending cancer for life. Our specialized care teams provide personalized, compassionate, expert care to patients of all ages. Informed by basic research done at our Sloan Kettering Institute, scientists across MSK collaborate to conduct innovative translational and clinical research that is driving a revolution in our understanding of cancer as a disease and improving the ability to prevent, diagnose, and treat it. MSK is dedicated to training the next generation of scientists and clinicians, who go on to pursue our mission at MSK and around the globe.

Exciting Opportunity at MSK: Postdoctoral fellow

The Romesser Lab is recruiting a bold, creative, and highly motivated Postdoctoral Fellow to join our team studying therapy-induced senescence, tumor immunology, and translational cancer biology.

Our laboratory is focused on turning cellular senescence into a therapeutically actionable immunologic state against cancer. Rooted in rectal cancer, but designed to translate across immune-refractory tumors, our program integrates immunocompetent mouse models, patient-derived organoids, tumor-immune co-culture systems, single-cell and spatial multi-omics, CRISPR-based functional genomics, and deeply annotated clinical specimens.

The successful candidate will have the opportunity to develop and lead NIH- and foundation-funded projects that dissect the senescence-immune interface and identify novel combination therapies that can be advanced toward clinical translation. The fellow will be expected to design, execute, optimize, and troubleshoot experiments across in vivo, ex vivo, and patient-derived model systems; integrate mechanistic and translational studies across mouse models, organoids, co-culture platforms, human tumor samples, and clinical biospecimens; analyze and interpret complex datasets; prepare manuscripts; present findings at scientific meetings; contribute to fellowship and grant applications; and collaborate across MSK's scientific community.

Our lab has access to exceptional translational resources, including a biobank of more than 500 patient-derived rectal cancer organoids, longitudinal tumor biopsies from patients undergoing therapy, and large clinical trial-associated biospecimen collections, including primary tumor and plasma samples. We are actively developing human organoid and T-cell co-culture systems using matched patient-derived samples, creating a powerful platform to study therapy response, immune resistance, and tumor-immune interactions in clinically relevant models.

What makes this opportunity distinctive is the direct connection between mechanistic laboratory science and active clinical investigation. The fellow will be able to move between patient-derived models, mouse systems, single-cell and spatial profiling, CRISPR-based perturbation approaches, and biospecimens from ongoing clinical studies, with the goal of identifying mechanisms of therapy response and translating these findings toward new therapeutic strategies.

This position is ideal for a candidate who wants to combine rigorous mechanistic biology with translational impact and who is excited to develop an independent scientific direction within a collaborative, technology-rich environment.

Core Skills:

• Experimental Design & Troubleshooting: Ability to conceptualize, execute, optimize, and troubleshoot complex in vivo, ex vivo, and patient-derived model systems, including mouse models, organoids, co-cultures, CRISPR perturbations, and multiplex assays.
• Tumor Immunology & Translational Biology: Experience with immunological assays such as flow cytometry, ELISA/LEGENDplex, T-cell or myeloid functional assays, tumor-immune co-culture systems, or related approaches.
• Data Interpretation & Multi-omic Integration: Ability to interpret complex biological datasets, including single-cell, spatial, functional genomics, flow cytometry, immune profiling, and clinical correlative data.
• Computational Experience Preferred: Experience with R, Python, Seurat, Scanpy, statistical analysis, data visualization, and/or machine learning approaches is preferred but not required. Candidates with strong wet-lab expertise and interest in working closely with computational collaborators are encouraged to apply.
• Scientific Communication & Leadership: Strong record of scientific communication, including manuscripts, presentations, collaborative project management, and mentorship of junior trainees.

Candidates are not expected to have expertise in all areas. We are especially interested in applicants with depth in one or more relevant disciplines, intellectual curiosity, strong experimental judgment, and a desire to learn new approaches.

International candidates are encouraged to apply. Visa and onboarding support are available through MSK's institutional processes.

Application Instructions

• Interested applicants should submit a CV, letter of interest, and contact information for references.
• The letter of interest should briefly describe the applicant's prior research experience, one example of a project or experiment they helped drive intellectually, their future scientific interests, and why they are interested in the Romesser Lab.
• Please send application materials to: Contact Name: Tiara Williamson. Contact Email: WilliT11@mskcc.org

PAY RANGE: $72,000 to $113,900

Helpful links:

• MSK Compensation Philosophy
• Review Our Great Benefits Offerings
• Romesser lab website

Closing:

At MSK, we believe in fair, competitive pay that reflects your job, experience, and skills.

MSK is an equal opportunity and affirmative action employer committed to diversity and inclusion in all aspects of recruiting and employment. All qualified individuals are encouraged to apply and will receive consideration without regard to race, color, gender, gender identity or expression, sexual orientation, national origin, age, religion, creed, disability, veteran status or any other factor which cannot lawfully be used as a basis for an employment decision.

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