Postdoctoral Fellow, Computational Biology in Cancer – Chan Lab at Memorial Sloan Kettering Cancer Center
About The Position
The Chan Lab in the Human Oncogenesis & Pathogenesis Program at Memorial Sloan Kettering Cancer Center is seeking a highly motivated and successful computational postdoctoral fellow to study the mechanisms and therapeutic implications of tumor cell plasticity. Our lab in translational computational oncology integrates single-cell and spatial genomics, cell-free DNA profiling, and machine learning to understand how tumors evolve under therapeutic and microenvironmental pressures. We leverage large, deeply annotated patient cohorts with longitudinal sampling, tightly coupled with functional preclinical models, to enable discovery and validation of mechanisms of tumor evolution. A central focus is lineage plasticity, the ability of cancer cells to transition between phenotypic states, which underlies metastasis, immune evasion, and drug resistance. Current research directions include: Defining transcriptional and epigenetic programs that drive lineage plasticity across adenocarcinoma, squamous, and neuroendocrine states in solid tumors Investigating analogous mechanisms of lineage switching in hematologic malignancies, including Richter’s transformation and myelofibrosis. Mapping immune and treatment-induced pressures that shape cell fate decisions across space and time Building predictive computational models of lineage transformation and therapeutic resistance through multi-modal data integration (scRNA-seq, ATAC-seq, spatial imaging, lineage tracing, cfDNA) This position offers the opportunity to work with deeply annotated patient cohorts, longitudinal samples, and cutting-edge experimental systems in a highly collaborative environment. We are seeking individuals who bring creativity, intellectual curiosity, and a strong drive to uncover underlying mechanisms, with a clear motivation to translate discoveries into improved patient care.
Requirements
- A PhD in Computational Biology, Bioinformatics, Computer Science, Statistics, or a related field
- Proficiency in Python and R
- Prior experience in computational biology
- Ability to engage in independent thinking
- Excellent skills in written and verbal communication
- Collegiality as a team member and a willingness to mentor other trainees
- At least 1 published first-author manuscript
Responsibilities
- Developing and applying computational methods
- Biological interpretation
- Assisting or leading in manuscript writing
- Engaging in a vibrant scientific community through regular work-in-progress and lab meetings, and other academic activities.
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What This Job Offers
Job Type
Full-time
Education Level
Ph.D. or professional degree
Number of Employees
1,001-5,000 employees
