MyGradJob
Postdoctoral
MyGradJob, Chapel Hill, North Carolina, United States, 27517
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.Job Description
We are 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 this kinase library. Working with researchers at SGC-UNC as well as SGC collaborators worldwide, the successful candidate will develop a comprehensive chemical genomics database of human protein kinases and their inhibitors, develop a new scheme for automated detection of kinase (subfamily)-specific chemotypes, and develop a 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.Qualifications
Minimum Qualifications: Qualified applicants must have extensive experience in the development and application of computational tools and methods for chemical and biological data mining. PhD in Bioinformatics or Cheminformatics.Additional Information
All your information will be kept confidential according to EEO guidelines.
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We are 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 this kinase library. Working with researchers at SGC-UNC as well as SGC collaborators worldwide, the successful candidate will develop a comprehensive chemical genomics database of human protein kinases and their inhibitors, develop a new scheme for automated detection of kinase (subfamily)-specific chemotypes, and develop a 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.Qualifications
Minimum Qualifications: Qualified applicants must have extensive experience in the development and application of computational tools and methods for chemical and biological data mining. PhD in Bioinformatics or Cheminformatics.Additional Information
All your information will be kept confidential according to EEO guidelines.
#J-18808-Ljbffr