Job:Assistant/Associate Professor of Computational Biology, Dana-Farber Cancer Institute (DFCI), Boston, MA, USA
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The Dana-Farber Cancer Institute (DFCI) and Harvard Medical School (HMS) seek an accomplished and innovative research faculty member to join the newly formed cBio Center at DFCI. The Center is an open and collaborative environment with a focus on computational biomedicine and cancer systems biology and is headed by Chris Sander. We provide an opportunity to pursue basic and translational research with an emphasis on solving biological problems using computational and data science methods, and to collaborate with cancer researchers and clinicians to impact clinical trials and cancer care in the age of genomically informed personalized medicine. The primary position will be in the Department of Biostatistics and Computational Biology at DFCI, with an academic appointment in the Department of Biomedical Informatics at HMS.

Particular areas of interest include:

  • machine learning and big data sciences
  • biomedical image analysis
  • phenotypic heterogeneity & single cell profiling
  • computational immunology

We also encourage strong applications in other areas of quantitative biology.

Requirements: a Ph.D. or M.D./Ph.D. degree and a significant record of asking good questions, advancing technology, making discoveries, and reporting these in peer-reviewed publications. Academic rank at Assistant or Associate Professor will be according to experience and productivity. Please send the following to chair@jimmy.harvard.edu: 1) a letter of application including a concise statement of past, current, and future research, 2) a curriculum vitae, 3) PDFs of your key publications (max four), and 4) contact information for four references. In addition, please ask your references to send letters of support to Giovanni Parmigiani, chair@jimmy.harvard.edu. Applications will be reviewed once the application package is complete.

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. We especially encourage women to apply.

immunology big-data machine-learning • 1.9k views
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