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美国西奈山伊坎医学院计算机辅助药物研发博士后职位

2021年08月16日
来源:知识人网整理
摘要:

美国西奈山伊坎医学院计算机辅助药物研发博士后职位

Icahn School of Medicine at Mount Sinai (ISMMS), MSHS

The Filizola Lab (http://www.filizolalab.org) at the Icahn School of Medicine at Mount Sinai, in New York City, USA is inviting applications for a postdoctoral research associate position in the broad field of computer-aided drug discovery. The laboratory is best known for contributing rigorous mechanistic insight into the structure, dynamics, and function of prominent drug targets such as G protein-coupled receptors (GPCRs), transporters, channels, transcription factors, and b3 integrins, for the ultimate purpose of accelerating drug discovery. To this end, we use several computational structural biology, cheminformatics, and artificial intelligence (AI)-based approaches, including molecular dynamics simulations, enhanced sampling methods, machine learning, deep learning, free-energy perturbations, molecular modeling, etc. Current ongoing projects include: discovery of novel chemotypes for a variety of prominent drug targets, binding and optimization of atypical opioid drugs, structure-based prediction of the efficacy of proteolysis-targeting chimaeras (PROTACs) for selective protein degradation, understanding functional selectivity of GPCRs at an atomic level of detail, predicting drug-target residence times as better indicators of in vivo drug efficacy than binding affinity, integrative structural modeling of intermediate conformations of ligand-protein complexes along protein’s activation pathway(s), etc.

The ideal candidate should have a Ph.D. or equivalent degree in a quantitative science major, including but not limited to Physics, Chemistry, Biophysics, Bioinformatics, Theoretical/Computational Chemistry, Computational Biology, Computer Science, Engineering, or a related discipline. To qualify for this position, a strong analytical ability is required alongside expert programming skills and a solid knowledge of molecular dynamics simulations, free energy calculations, machine learning/deep learning, Markov State Models, virtual screening, docking, pharmacophore analysis, etc. Strong communication skills and an ability to both collaborate with peers and train junior colleagues effectively are also required. The position is available immediately.

Qualified applicants should send a CV and at least 2 reference names by email to Dr. Marta Filizola at marta.filizola@mssm.edu. Review of applications will begin immediately and continue until the position is filled.