Post-Doc Research Associate
Department
Pharmacology - 424001
Position Summary
The Miao Lab in the Computational Medicine Program and Department of Pharmacology at the University of North Carolina – Chapel Hill (https://www.med.unc.edu/pharm/directory/yinglong-miao/) is looking for two highly motivated Postdoctoral fellows to work on accelerated molecular simulations and AI-driven drug discovery.
Research projects in the Miao Lab include development of novel theoretical and computational methods and AI techniques for accelerated simulations of biomolecular recognition (such as drug binding and protein-protein interactions) and cellular signaling, and cutting-edge applications in drug discovery of critical targets including G-protein-coupled receptors (GPCRs), membrane-embedded proteases, RNA-binding proteins and RNA. In collaboration with world-leading experimentalists in pharmacology, structural biology, biochemistry and medicinal chemistry, the new postdoc will have the opportunity to work on unprecedented simulations and AI-driven drug discovery of functionally important biomolecules for treatments of neurological disorders, heart failure and cancers.
Minimum Education and Experience Requirements
A Ph.D. and/or M.D. in biomedical or related sciences is required.
Required Qualifications, Competencies, and Experience
The position requires knowledge and training in computational biophysics/chemistry and drug design. The researcher will conduct research to forward the developments of biomolecular modeling and computer-aided drug design. The researcher will also be engaged in developing proposals for new funding sources, publishing and presenting research topics as applicable.
Preferred Qualifications, Competencies, and Experience
Candidates are expected to have strong publication record in biomolecular modeling and computational biophysics/chemistry. Programming skills (e.g., bash scripting, python, Fortran, C++ and CUDA), expertise in computational modeling (such as Molecular Dynamics, virtual screening, free energy calculations and Deep Learning), successful experimental collaboration experiences and excellent communication skills are preferred.
Special Instructions
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