Postdoctoral Research Position in Quantitative Sciences for Cancer Research

Cambridge, Massachusetts (US)
Friday, 6 December 2019
End of advertisement period
Sunday, 5 January 2020
Contract Type
Fixed Term
Full Time

School Harvard T.H. Chan School of Public Health
Department/Area Biostatistics

The Department of Biostatistics at the Harvard T.H Chan School of Public Health invites applications for a Postdoctoral fellow position funded in large part by an NIH training grant on Quantitative Sciences for Cancer Research. Candidates have latitude to choose among several mentors across various institutes at Harvard; research can range from the most applied to the most theoretical as long as there is a genuine commitment to its ultimate utility in cancer research.

Basic Qualifications

The ideal candidate is an independent, solution-oriented thinker with a strong quantitive background and a clear commitment to cancer research. Other qualifications include:

  • Preferred PhD in Statistics, Biostatistics, Computer Science, Data Science, or related field
  • Required: U.S. Citizenship or Permanent Residency
  • Preferred: Interest in developing open-source software, reproducibility.
  • Preferred: Familiarity with multiple data science tools and ability to learn new tools as required.
  • Preferred: Excellent communication and writing skills.

Special Instructions Information on resources for career development and work/life balance at SPH can be found at: https://cdn1.sph.harvard.edu/wp-content/uploads/sites/40/2013/08/BeneSummPostdoc2015.pdf

The application should include an indication of which preceptor or preceptors would be the candidate’s preferred choice. The list of preceptors can be found at https://sites.sph.harvard.edu/cancer-training-grant/directors/

Contact Information Application questions regarding this position can be sent to Susan Luvisi at sluvisi@hsph.harvard.edu.

Equal Opportunity Employer We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions or any other characteristic protected by law.

Minimum Number of References Required 2
Maximum Number of References Allowed 5