Computational Genetics Fellow


Memorial Sloan Kettering Cancer Center (MSK) is one of the world’s premier cancer centers, committed to exceptional patient care, leading-edge research, and superb educational programs. The blending of research with patient care is at the heart of everything we do. The institution is a comprehensive cancer center whose purposes are the treatment and control of cancer, the advancement of biomedical knowledge through laboratory and clinical research, and the training of scientists, physicians and other health care workers. At MSK, we’re not only changing the way we treat cancer, but also the way the world thinks about it. By working together and pushing forward with innovation and discovery, we’re driving excellence and improving outcomes.

For the 28th year, MSK has been named a top hospital for cancer by U.S. News & World Report. We are proud to be on Becker’s Healthcare list as one of the 150 Great Places to Work in Healthcare in 2018, as well as one of Glassdoor’s Employees’ Choice Best Place to Work for 2018. We’re treating cancer, one patient at a time. Join us and make a difference every day. 

The ideal candidate for the Computational Genetics postdoc position would have skills in population genetics theory or gene mapping of complex traits. Some experience with computer programming such as PERL/Python/R and basic Unix/Linux skills are necessary. Experience with data wrangling of large-scale datasets either on local machines, compute clusters or cloud computing environment is necessary. If you have worked with non-human or model organisms but want to transition to translational human disease research, we encourage you to apply.

The projects currently open to enthusiastic and motivated candidates who thrive in a fast-paced environment are:

  • Large agnostic gene hunting in familial and early onset bladder cancer and multiple myeloma.
  • Family based gene discovery in the setting of one of the largest hereditary cancer genetics service.
  • Methods development that bridge the gap between research and clinical applicability such as PathoMAN.

Application Requirements

Please send CV, a letter outlining your interest and names/contact information of three references via email to: [email protected]