Systems Pharmacology Postdoctoral Position


The Laboratory of Systems Pharmacology at Harvard Medical School is seeking a talented, highly motivated and energetic postdoctoral fellow with expertise in computational biology. The aim of the project is development of a new mathematical, computational and systems-level understanding of toxicology and pharmacology. Progress in this area will have not only fundamental scientific impact but also accrue immediate, broad practical benefits for the discovery of new therapeutic agents and biomarkers.

The candidate will work primarily in the Vaidya Group and has access to the resources made available through the Harvard Program in Therapeutic Sciences. The candidate will work alongside members of the Laboratory of Systems Pharmacology that includes cell and computational biologists, engineers and physicists to develop new algorithms, methods and models to build predictive and explanatory network models of toxic responses. Experimental modalities include measuring time- and dose-resolved drug toxic responses by large-scale genomic-level RNA sequencing, proteomics and high content imaging. The postdoctoral fellow is expected both to undertake an independent research project and support the efforts of the lab as a whole.

Analysis, hypothesis generation and formulation of explanatory models will rely heavily on mathematical methods, including linear and non-linear dimensionality reduction, classifiers and regression models drawn from machine learning and statistics.

Qualifications and Skills:

  • Candidate should have doctoral degree in Systems Biology, Bioinformatics, Theoretical Biology, Computer Science, Computational Biology, Biostatistics, Applied Mathematics, Chemistry, Physics or related quantitative, data-heavy discipline.
  • Experience applying and developing mathematical and computational algorithms for large datasets.
  • Experience with machine learning and statistical analysis is preferred, e.g. support vector machines, random forests, stacked classifiers, deep learning neural networks, nearest neighbor classifiers.
  • Proficiency in one or more mathematical frameworks (e.g. Python, MATLAB, R) appropriate for scalable data analysis.
  • Understanding of cell biology, biochemistry, and molecular biology. Research experience in toxicology, kidney biology is preferred but not necessary.
  • Understanding of experimental techniques in modern biology, e.g. tissue culture, expression profiling, immunofluorescence.
  • Ability to work as part of a team and independently.
  • Skillful English writing ability with first author publications in peer reviewed journals.
  • Strong oral communication skills.

This is a 2 year position and which start as early as October 1, 2015.

To apply, please e-mail CV, cover letter and contact information for three references to Dr. Vaidya: