Postdoctoral Research Fellow, Computational and Mathematical Modeling, Cancer Immunology, Genentech Research

Job ID:
Job date: 2018-06-03
End Date: 2018-08-02

Company : Genentech 

Country : United States 

Role : Postdoc 


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Job Description:
We are seeking an independent and motivated researcher for a Postdoctoral Fellowship in the Department of Cancer Immunotherapy. You will be working within our Computational and Mathematical Modeling group to study cancer phenotypes and the interaction with genetic and immune system variables. For example, you will participate in trying to deepen our understanding of the dynamics within tumor microenvironments supported by unique and growing collections of Omics data coupled with clinical data.

Your primary goals will be scientific discovery and publication (see http://www.gene.com/careers/academic-programs/postdocs), and the program is geared towards developing the career of future independent investigators.

Candidates for this position should have:

  • PhD in Mathematics, Mathematical Statistics, Computer Science or Bioinformatics with a proven track record in mathematical modeling.
  • Highly proficient in general in computational and programming languages, including a working knowledge of R and e.g Python. Experience with C++ would be an asset.
  • Experience with creating web-based data visualization and data analysis applications (e.g. R Shinys) is desirable.
  • Desirable having a previous experience working with biologists on life-science questions.
  • Excellent communication and teamwork skills to take advantage of our highly collaborative environment.
  • A passion for innovation, and demonstrated initiative and track record in tackling new areas of research.


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Additional Info:
Biomedical research has become data intensive, shifting away from classical confirmatory hypotheses testing for a few clinical variables, to searching for underlying fundamental patterns governing biological phenomena and their dynamics in high dimensional variable and sample space. This has led to an increasing use of, and development of new, computational and mathematical modeling techniques within biomedicine.

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