Postdoctoral Fellow - Therapeutic Senescence & Tumor Immunology Laboratory of Paul Romesser, MD

Postdoctoral Fellow – Romesser Lab

Mission-driven research at Memorial Sloan Kettering Cancer Center focuses on turning therapy‑induced senescence into a therapeutically actionable immunologic state against cancer. The Romesser Laboratory seeks a bold, creative, and highly motivated Postdoctoral Fellow to develop and lead NIH‑ and foundation‑funded projects that dissect the senescence‑immune interface and identify novel combination therapies for translational advancement.

• Design, execute, optimize, and troubleshoot experiments across in vivo, ex vivo, and patient‑derived model systems, including immunocompetent mouse models, patient‑derived organoids, tumor–immune co‑culture platforms, and CRISPR‑based functional genomics.
• Integrate mechanistic and translational studies using a variety of systems to analyze complex datasets from single‑cell, spatial multi‑omics, flow cytometry, and clinical biospecimens.
• Prepare manuscripts, present findings at scientific meetings, and contribute to grant applications.
• Collaborate across Microsoft Sloan Kettering’s scientific community, leveraging access to a biobank of over 500 rectal cancer organoids, longitudinal tumor biopsies, and large clinical trial biospecimen collections.

• PhD, MD/PhD, MD, or equivalent doctoral degree in immunology, cancer biology, molecular biology, cell biology, computational biology, or a related field.
• Strong record of scientific productivity, including first‑author publications or clear evidence of major manuscript‑level contributions.
• Demonstrated ability in an area such as tumor immunology, cancer biology, organoid systems, mouse models, senescence biology, cancer metabolism, CRISPR screening, single‑cell/spatial biology, or computational biology.
• Proficiency in experimental design, troubleshooting, and the use of complex model systems, including flow cytometry, ELISA/LEGENDplex, T‑cell/myeloid functional assays, and multiplex assays.
• Capability to interpret and integrate multi‑omic datasets, with preferred experience in R, Python, Seurat, Scanpy, statistical analysis, data visualization, or machine learning.
• Strong scientific communication skills and enthusiasm for collaborative translational research. Depth in one or more disciplines is preferred over broad but superficial experience.
• Ability to interpret complex biological datasets, collaborate in interdisciplinary teams, and manage projects.

Visa and onboarding support are available through MSK’s institutional processes.

The University is an equal opportunity and affirmative action employer committed to diversity and inclusion. All qualified individuals are encouraged to apply. No regard shall be given to race, color, gender identity or expression, sexual orientation, national origin, age, religion, creed, disability, veteran status, or other protected characteristics.