Computational Biologist

We are looking for a computational biologist to develop the pipeline for analyzing data generated from circulating nucleic acids (DNA/RNA) in body fluids, or so-called “Liquid Biopsy”,  (plasma, urine, CSF) of different cancer types.

Description of this role

The successful candidate will participate in projects to achieve 3 goals: (1) develop analysis pipeline for massively parallel sequencing (MPS) / next-generation sequencing (NGS) assays to profile circulating tumor DNA (ctDNA) from body fluids and (2) evaluate its utility in different solid cancer types (3) study the biological characteristics of circulating tumor DNA in body fluids. (Research focuses of the lab are here).

For (1), the types of assays we develop include targeted DNA sequencing, exome sequencing, whole genome sequencing, or DNA methylation, 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 FFPE or 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.

For (2 and 3), 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.

More information about postdoctoral training at MSKCC:

Mailing Address

Dana Tsui, PhD
c/o Yesenia Werner
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.

Address all informal inquiries to Yessie Werner at or at 646-888-3540.