Postdoctoral Research Scholar in Computational Oncology – Jake Lee Lab

Memorial Sloan Kettering Cancer Center • New York, NY

3d • Onsite

About The Position

The Jake Lee Lab at Memorial Sloan Kettering Cancer Center (MSK) is seeking a highly motivated postdoctoral fellow with strong expertise in computational biology. This role will focus on studying the mutational processes and genomic rearrangements that drive cancer evolution and therapy resistance using high-throughput sequencing. The project involves analyzing single-cell whole-genome sequencing data along with other multi-omic datasets from mouse models, PDX/PDO systems, and clinical tumor samples to define evolutionary trajectories of extrachromosomal circular DNA-mediated oncogene amplification. This position offers a unique opportunity to work in a highly collaborative and translational environment, closely partnering with experimental scientists and clinician investigators. The position is supported by a grant from the Burroughs Wellcome Fund.

Requirements

• PhD in Computational Biology, Bioinformatics, Genomics, Computer Science, or a related field OR MD with substantial research training in quantitative biology and a strong publication record
• Strong programming skills in Python and/or R
• Experience in high-throughput sequencing data analysis
• Familiarity with Unix/Linux environments and version control

Nice To Haves

• Prior experience with single-cell genomics and/or cancer genomics is highly desirable
• Deeply motivated to understand how cancer cells evolve, both intrinsically and under therapeutic pressure
• Passionate about applying computational approaches to answer fundamental biological and clinically relevant questions
• Actively follows and critically engages with both classic and recent studies in the scientific literature
• Experienced in working with large-scale sequencing datasets and developing reproducible, well-documented analytical workflows
• Detail-oriented, able to identify systemic biases in data and quickly identify their source
• Collaborative, with the ability to communicate effectively across computational, experimental, and clinical disciplines

Responsibilities

• Lead computational analyses of high-throughput sequencing datasets, including scWGS and multi-omic datasets
• Apply/adapt/develop novel computational approaches to study mutational processes, structural variation, and clonal evolution in cancer
• Collaborate on experimental design and interpretation with wet-lab and clinical teams
• Integrate genomic data with rich clinical annotation to uncover biologically and clinically meaningful insights
• Drive preparation of high-impact manuscripts and present findings at major conferences
• Help shape new research directions at the intersection of cancer genomics and therapy resistance

Benefits

• Fair, competitive pay that reflects your job, experience, and skills

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree