Postdoctoral Researcher - Computational Chemistry

Postdoctoral Researcher - Computational Chemistry

The Acharya group (ACompChemLab) uses multiscale computational modeling to investigate complex biological systems spanning bacteria, viruses, and light-sensitive proteins, particularly emphasizing the native protein, lipid, and sugar environments. More details about ACompChemLab may be found at The postdoctoral associate is expected to participate in these projects. The successful candidate will have Dr. Acharya's support for their career development efforts, including attempting to get independent research funding. The candidate will have access to the resources available to ACompChemLab to do so. The initial appointment will be for 1-year and renewable upon mutual agreement based on an annual performance review and funding availability.

Qualifications: Ph.D. in Chemistry, Biochemistry, Biophysics, Biomedical Engineering, Chemical Engineering, or related subjects. Experience in electronic structure theory, QM/MM simulations, and/or MD simulations. Experience with building machine learning models in a biochemical context. Experience in coding and scripting (e.g., python, tcl). Familiarity with at least one molecular dynamics package (e.g., NAMD, AMBER, CHARMM, GROMACS, etc.). Experience in working with biochemical/biophysical systems or processes. In-depth knowledge and experience with Python libraries for machine learning and data science. Experience with at least one molecular visualization package (e.g., VMD, PyMOL, UCSF Chimera, etc). Ability to work as an independent scientist.

Responsibilities: Prepare biochemical systems in their native environments and perform equilibrium and non-equilibrium molecular dynamics simulations, including free-energy calculations for systems studied by Dr. Acharya's group (ACompChemLab). Set up and perform electronic structure and multiscale QM/MM calculations. Build a database for machine learning models and develop models for electronic properties. Perform network analysis and build machine learning models relevant for allosteric processes. Provide technical help to other students and prepare presentations. Write and publish peer-reviewed research papers and assist Dr. Acharya, as required. Travel and present research at conferences, as appropriate.