Working at MIT offers opportunities, an environment, a culture - and benefits - that just aren't found together anywhere else. If you're curious, motivated, want to be part of a unique community, and help shape the future - then take a look at this opportunity.

POSTDOCTORAL ASSOCIATE, Biological Engineering-Tissue Chips in Space Project, to join the team of Dr. Murat Cirit and Professor Alan Grodzinsky. The Tissue Chips in Space program will focus on human physiology and disease onboard the International Space Station (ISS) U.S. National Laboratory. Data from this translational research--which will feature "tissue chips" (or "organs-on-chips")--will help scientists develop and advance novel technologies that benefit human health on Earth and in space. The MIT research focuses on a cartilage-bone-synovium joint tissue chip model to study the effects of space flight on musculoskeletal disease biology. Duties include working with postdocs and technical staff to support original research in post-traumatic osteoarthritis (PTOA), which may include computational analysis of metabolomics and proteomics data, developing algorithms for patient stratification for selected drugs, biostatistical analysis of therapeutic drug intervention in in vitro systems, translation of in vitro results to in vivo clinical outcomes, and developing algorithms to understand effects of micro-gravity on drug efficacy.

Job Requirements
REQUIRED: Ph.D. in engineering, statistics, or relevant field; post-graduate experience in the biological field; experience with computational modeling of biological networks with large data set (-omics) and knowledge of currently used computational approaches; expertise in biological network construction, multi-scale modeling, and the integration of multiple datatypes including metabolomics and proteomics; experience with a variety of computational biology techniques, software packages (R, MATLAB, Python), -omics databases, and algorithms to analyze -omics data; ability to work independently and collaboratively in fast-paced environment with competing priorities; and strong publication record. Experience with mechanistic models (PKPD, PBPK, and ODE- and PDE-based) and experience developing analytical workflows for metabolomics or proteomics data sets a plus. Job #14881


6/19/17

MIT is an equal employment opportunity employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, sex, sexual orientation, gender identity, religion, disability, age, genetic information, veteran status, ancestry, or national or ethnic origin.



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