Atanu Acharya

Syracuse University’s ACompChemLab is recruiting a Postdoctoral Researcher in Computational Chemistry focused on multiscale modeling , QM/MM , molecular dynamics , and machine learning for biosystems . The position is based in the Acharya group at Syracuse University and involves studying complex biological systems such as bacteria, viruses, and light-sensitive proteins, with emphasis on native protein, lipid, and sugar environments. The successful candidate will work on preparing biochemical systems in native environments, running equilibrium and non-equilibrium MD simulations, performing free-energy calculations, setting up electronic structure and multiscale QM/MM calculations, building databases for ML models, developing models for electronic properties, and carrying out network analysis related to allosteric processes. The role also includes helping other students, preparing presentations, publishing peer-reviewed papers, and presenting at conferences. Eligibility highlights: Ph.D. in Chemistry, Biochemistry, Biophysics, Biomedical Engineering, Chemical Engineering, or a related field; experience in electronic structure theory, QM/MM and/or MD simulations; machine learning in a biochemical context; coding/scripting (Python, Tcl); familiarity with at least one MD package (NAMD, AMBER, CHARMM, GROMACS, etc.); experience with biochemical/biophysical systems; Python ML/data science libraries; and molecular visualization tools such as VMD, PyMOL, or UCSF Chimera. Funding: Full-time postdoc with a salary range of $62,400-$67,400. The initial appointment is for one year and may be renewed depending on performance and funding availability. Dr. Acharya also indicates support for career development and efforts to secure independent research funding. How to apply: Submit the online application through Syracuse University’s employment site. Attach a CV, cover letter, and three references. The posting is open until filled, so early application is advisable. Research keywords: computational chemistry, multiscale modeling, QM/MM, molecular dynamics, machine learning, biophysical chemistry, allostery, free-energy calculations, electronic structure, biosystems.