postdoc in OMICS + Machine Learning + Drug Discovery

Michigan State University
Pediatrics/Pharmacology/Computer Science
United States MI Grand Rapids


The Bin Chen Laboratory uses big data and artificial intelligence to discover new or better therapeutic candidates. The lab has collected over 30,000 bulk RNA-Seq profiles, millions of single-cell RNA-Seq profiles, and millions of drug-induced gene expression profiles and has started to routinely generate spatial transcriptomics data. The lab is now capable of screening drug candidates from millions of novel compounds for diseases based on gene expression. Our postdoctoral fellow will help refine the models and translate these data points into therapeutics. The lab works on the following diseases: liver cancer, DIPG, melanoma, Alzheimer’s, and COVID-19 and is open to study other conditions.  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 model,  (2) developing interpretable machine learning methods to predict drug-induced gene expression profiles and elucidate drug mechanism of actions, (3) developing deep reinforcement learning models in lead optimization, (4) developing and implementing new computational methods to leverage spatial transcriptomics in target discovery. The candidate will closely work with computer scientists to develop models and bench scientists to validate drug hits. The candidate could be strong in either medicinal chemistry/biology or bioinformatics/machine learning. Recent Chen Lab work has been published in Gastroenterology, Nature Communications, Nature Protocols, Nature Reviews Gastroenterology and Hepatology, ICDM, and KDD and featured in STAT, GEN, GenomeWeb, and KCBS. As two lab senior members are leaving to start their own lab, we are actively looking for new postdocs to take over their projects. We are particularly interested in the candidate who plans to become a PI after the training. Please apply through
The lab is also seeking a data scientist to mine electronic health records. If you are interested in this position, please apply through
Papers related to this position:
Chen B#, Garmire L, Calvisi DF, Chua M-S, Kelley RK, Chen X. Harnessing big ‘omics’ data and AI for drug discovery in hepatocellular carcinoma, Nat Rev Gastroenterol Hepatol.  2020 Jan 3. doi: 10.1038/s41575-019-0240-9. PMID: 31900465
#Billy Zeng, #Benjamin S. Glicksberg, #Patrick Newbury, #Evgenii Chekalin, Jing Xing, Ke Liu, Anita Wen, Caven Chow, Bin Chen, OCTAD: an open workspace for virtually screening therapeutics targeting precise cancer patient groups using gene expression features, Nat Protoc., 2020 Dec 23. doi: 10.1038/s41596-020-00430-z. PMID:33361798
Mengying Sun, Jing Xing, Bin Chen, Jiayu Zhou, Robust Collaborative Learning with Noisy Labels, ICDM, 2020
Mengying Sun, Jing Xing, Huijun Wang, Bin Chen, Jiayu Zhou, MoCL: Contrastive Learning on Molecular Graphs with Multi-level Domain Knowledge, KDD, 2021


PhD with at least two first-author publications in computational biology or computational chemistry

Start date

As soon as possible

How to Apply

apply through


Bin Chen