02 Oct Two Postdoc Positions Available
Postdoctoral Research Associate – Cheminformatics/Data Science
Postdoctoral position is available at Wake Forest Institute for Regenerative Medicine (Winston-Salem, NC) for industry-sponsored cheminformatics project with a focus of application of Deep Learning to chemical and biological data.
Educational Requirements: PhD in Bioinformatics, Cheminformatics or Computer Science
Desired experience: Cheminformatics analysis of small molecules (SAR/QSAR, data mining, ligand-based similarity assessment) structure-activity relationships. Bioinformatics analysis of biochemical and molecular biological data (screening data, in vivo/in vitro assays, pathways, gene expression profiles, etc). Chemogenomic analysis and prediction of protein-ligand interactions (protein structure analysis, ligand binding site comparison, molecular docking simulations, molecular interaction analysis, homology modeling). The ideal candidate has significant experience in computer programming using different programming languages in order to develop new cheminformatics and bioinformatics approaches and corresponding analysis tools. Strong publication record.
Desired skills: Practical knowledge of machine learning, especially Deep Learning. Excellent programming (Python/R) skills. Excellent verbal and written communication skills.
The following will be considered an advantage: Experience in the construction of bioinformatics and cheminformatics/chemogenomics databases is a strong advantage. Familiarity with Web service technologies, RESTful APIs. Experience with any data integration technologies / “Big Data” solutions. Exposure to natural language processing, especially text mining.
Apply: Please send cover letter and CV to Dr. Olexandr Isayev at email@example.com
Postdoctoral Research Associate – Cheminformatics
The Structural Genomics Consortium at the University of North Carolina at Chapel Hill (SGC-UNC) and the Laboratory for Molecular Modeling at the UNC Eshelman School of Pharmacy are interested in recruiting a postdoctoral fellow in computational chemical genomics. The project entails the rational expansion of the GSK Published Kinase Inhibitor Set (PKIS) to enrich the current collection of de-orphanized human protein kinases and unique chemical probes for thus kinase library. Working with researchers at SGC-UNC as well as SGC collaborators worldwide, the successful candidate will develop comprehensive chemical genomics database of human protein kinases and their inhibitors, develop new scheme for automated detection of kinase (subfamiliy)-specific chemotypes, and develop predictive understanding of structure-activity and structure-selectivity relationships for kinase inhibitors to identify selective kinase-specific putative probe compounds. The ultimate objective of this computational project is to prioritize new compounds for experimental testing.
This postdoctoral fellow position will be part of a multidisciplinary team that includes biologists, chemists, and data scientists. The ideal candidate will have significant expertise in bioinformatics and cheminformatics, working knowledge of multivariate statistical and data mining techniques, and strong programming skills. Experience with developing and maintaining large databases is a plus.
Educational Requirements: PhD in Bioinformatics or Cheminformatics
Qualifications and Experience: Qualified applicants must have extensive experience in development and application of computational tools and methods for chemical and biological data mining.
Apply online: https://unc.peopleadmin.com/postings/84607
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