Computational Biologist


Description of this role

We are looking for a computational biologist to join our team to

(i) study the clinical utility of cell-free DNA and RNA in cancer types including patients with MSI-high tumor (pan-cancer), prostate cancer, breast cancer, ovarian cancer, lung cancer, clear cell renal cancer, liver cancer, pediatric cancers and lymphoma patients; and

(ii) study the incorporation of mutation detection by targeted sequencing and fragment size analysis in whole genome sequencing of cell-free DNA for the noninvasive detection of minimal residual disease in cancer patients

(Research focuses of the lab are here).

The types of assays we develop include targeted DNA sequencing, whole genome sequencing,  DNA methylation, or cell-free RNA, depending on tumor types and the genomic coverage/detection sensitivity required for different clinical questions. Prior experience on analysis of MPS or NGS assays is necessary, preferably on data generated from body fluids (plasma, urine, saliva, CFS) in pregnancy or pathological conditions (not limited to cancer). Basic understanding of the sequencing library preparation workflow (different molecular strategies, such as capture, targeted etc) is preferable.

We work with clinical trial teams and research groups specialized in a variety of solid tumors across MSKCC to address different questions (examples here – we collect longitudinal samples and aim to compare ctDNA dynamics with clinical responses to evaluate its informatively on treatment decision.  The possible cancer types include: prostate, breast, brain, bladder, lung and ovarian, and the list is expanding. Experience on data analysis related to calling variants (point mutations / indel / structural rearrangement / copy number changes) or bisulfite DNA methylation (any of the above) will be necessary. Basic understanding of cancer genomics will be preferable.

The development of analysis pipeline will be a jointed effort with the computational team(s) of the Innovation Laboratory of the Center for Molecular Oncology and the Molecular Diagnostics Service team. Clinical evaluation will be done in close collaboration with individual research groups and clinical trials teams. The ideal candidate will be a team-player with excellent communication and interpersonal skills.

Other information

Computational techniques:

  • Experience with programming skill, such as R, Python, MatLab, etc.
  • Analysis of NGS/MPS data – targeted/exome/whole genome sequencing, or DNA methylation (bisulfite sequencing data, or relevant)
  • Variant calling – point mutations, indel, structural rearragenement, copy number changes
  • Building analysis pipeline, basic genomic sequencing alignment

Statistical knowledge:

Knowledge of biomedical statistics and experience with statistic programmes such as R, SPSS, Prism, etc.

We are not looking for someone who only follows protocols. We want an inventor with a creative mind. Join us if you think you are good and want to make an impact.

Memorial Sloan Kettering Cancer Center is an equal opportunity employer with a strong commitment to enhancing the diversity of its faculty and staff. Women and applicants from diverse racial, ethnic and cultural backgrounds are encouraged to apply.

We welcome application for postdoctoral fellowship. More information about postdoctoral training at MSKCC:

Mailing Address

Dana Tsui, PhD
Memorial Sloan Kettering Cancer Center
1275 York Avenue, Box 20
New York, NY 10065

Application Requirements

If you are interested in joining our lab, please submit your curriculum vitae and a cover letter detailing your past research experience, accomplishments, current motivation and future research interests. Include your expected availability date and the names and contact information of three referees.