Postdoctoral Research Scholar in Computational Oncology – Jake Lee Lab

Memorial Sloan Kettering Cancer Center • New York, NY

7d

About The Position

About Us: 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. Join the Lee Lab: Cancer Genome History & Therapeutics at MSK. We study the mutational processes and genomic rearrangements that drive cancer evolution and therapy resistance using high-throughput sequencing as the main toolkit. We are seeking a highly motivated postdoctoral fellow with strong expertise in computational biology to lead projects at the interface of cancer biology, single-cell genomics, and clinical oncology. Project focus: You will analyze single-cell whole-genome sequencing data jointly with other multi-omic datasets from i) genetically engineered mouse models, ii) PDX/PDO systems, and iii) 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. https://www.mskcc.org/profile/jake-june-koo-lee What you will do: 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 Who you are: 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 Who we are: The Lee Lab is a newly established computational research group within MSK Computational Oncology focused on the mutational mechanisms and rearrangement processes that drive cancer genome evolution. We seek to uncover how and why cancer genomes acquire their complex architectures and how they continue to evolve in patients undergoing treatment. Ultimately, our goal is to identify strategies to intercept this maladaptive evolution and restore physiology. Our most recent story here: https://www.biorxiv.org/content/10.64898/2026.02.12.705658v1 Our work leverages cutting-edge sequencing technologies, including single-cell whole-genome sequencing, long-read sequencing, and multi-omic approaches. Beyond applying state-of-the-art methods, we actively adapt and extend them to address fundamental questions in cancer biology. Many of our projects are in collaboration with experimental investigators. We are committed to building a collaborative, supportive, and intellectually vibrant lab environment.

Requirements

• One of the following academic qualifications: PhD in Computational Biology, Bioinformatics, Genomics, Computer Science, or a related field 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

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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree
• Number of Employees: 1,001-5,000 employees