The Bin Chen Laboratory (binchenlab.org) uses big data and artificial intelligence to discover new or better therapeutic candidates. The lab has collected over 30,000 bulk RNA-Seq profiles and millions of single-cell RNA-Seq profiles and drug-induced gene expression profiles. The lab is now capable of screening drug candidates from millions of novel compounds for a given disease gene expression signature. Our postdoctoral Research Associate will help refine the models and translate these data into therapeutics. In addition, the successful candidate is expected to lead or assist with any of the following projects: (1) Developing deep learning and transfer learning algorithms to discover novel therapeutics and transfer knowledge between preclinical and clinical models and (2) Improving and implementing a systems-approach (octad.org) to discover therapeutics for various diseases.
The Chen Lab is located along the Medical Mile in beautiful downtown Grand Rapids. Our Secchia Center facilities are modern and comfortable. We are a welcoming team with members from all over the world. Our work depends on close collaborations with outstanding bench scientists, data scientists, and clinicians; the successful candidate will have the opportunity to form strong working relationships at Michigan State University, Van Andel Research Institute, Spectrum Health, the University of California Berkeley, the University of California San Francisco, and Stanford University. Recent Chen Lab work has been published in Gastroenterology, Nature Communications, Nature Protocols, and Nature Reviews Gastroenterology and Hepatology, and featured in STAT, GEN, GenomeWeb, and KCBS.
Ph.D. or M.D./Ph.D. in Bioinformatics, Chemical Informatics, Biostatistics, Statistics, Computational Biology, Informatics, Computer Science, or a related field.
Strong experience with machine learning/statistical learning
Prior evidence of productivity, creativity, and passion for drug discovery
Excellent communication skills in English
Proficiency in using R/Bioconductor and Python (in particular Pytorch)
Strong background in cancer genomics and computational drug discovery