The Harvard Medical School Laboratory of Systems Pharmacology is seeking a postdoctoral level computational biologist to work on a DARPA-funded project (https://www.darpa.mil/news-events/2018-11-28) to develop novel experimental and computational platforms that accelerate drug discovery in the area of pain and inflammation. The role will bridge the experimental and computational aspects of the project to identify possible drug targets by applying network-guided inference to phenotypic assays for pain modulators. The postdoc will be mentored by Dr. Peter Sorger and will work as part of an interdisciplinary team developing tools for automated reasoning to accelerate scientific discovery (https://indralab.github.io).
The ideal candidate will have prior experience in neurobiology or other fields related to pain and inflammation. Responsibilities will include integrating data generated across multiple labs and assays (imaging, electrophysiology, transcriptomics and proteomics), analyzing it with in-house software tools, and interpreting the results to prioritize follow-up experiments. Programming and data analysis experience in Python preferred.
Internal Number: 1
About Harvard Medical School Lab of Systems Pharmacology
The Harvard Medical School (HMS) Laboratory of Systems Pharmacology (LSP) is a NIGMS Center for Systems Biology multi-disciplinary effort within the Harvard Program in Therapeutic Science (HiTS) to reinvent the fundamental science underlying the development of new medicines and their use in individual patients. Every cell is an extensively interconnected ecosystem. Any given gene may influence dozens or hundreds of other genes. Systems Pharmacology investigates drug action at the level of entire biochemical and genetic networks, rather than looking at the effect of any single element. The LSP brings together investigators in mathematical and experimental disciplines from multiple academic institutions (Harvard, MIT, Tufts) and research hospitals (Dana Farber, MGH, BWH) and eventually visiting scientists from the FDA and local drug companies to integrate computational and systems approaches into all phases of drug discovery and development.