Postdoctoral Scholar in Computational Biophysics

CHARMM is a versatile program for atomic-level simulation of
many-particle systems, particularly macromolecules of
biological interest. - M. Karplus

Postdoctoral Scholar in Computational Biophysics

Date

2026-10-01

Location

University of California, Merced

Description

The Dutagaci Lab at the University of California, Merced is seeking a postdoctoral scholar to work on an NIH-funded project (Project Number: R35GM163973) focused on biomolecular simulations and machine learning applications in biological systems. The Postdoctoral Scholar will conduct mentored research under the supervision of the PI and investigate transcription by studying the structure and dynamics of RNA polymerase to address mechanistic questions related to the roles of elongation factors and their connection to human diseases.

Responsibilities

• Conduct research in computational biophysics related to the project, using standard and enhanced sampling molecular dynamics simulations and machine learning approaches.
• Participate in manuscript preparation and dissemination of research findings through presentations at scientific conferences and publications in peer‑reviewed journals.
• Participate in professional development activities such as scientific conferences and meetings.
• Assist in mentoring graduate and undergraduate students under the supervision of the PI at Dutagaci Lab.

The position is available immediately. The initial appointment is for two years, with the possibility of extension for up to a total of five years, contingent upon satisfactory performance and the availability of funding.

Qualifications

• Basic qualifications:
  • Ph.D. in Chemistry, Biochemistry, Biology, Physics, or related fields.
  • Experience working in a Linux environment.
  • Experience in one or more programming languages such as Python, Perl, C, or Fortran.
  • Experience in one or more molecular dynamics simulation software such as CHARMM, OpenMM, NAMD, or GROMACS.
  • A record of peer‑reviewed research publications.
• Preferred qualifications:
  • Experience with machine learning and statistical analysis methods.
  • Graduate‑level training in computational biophysics or physical chemistry.
  • Experience in biomolecular simulations.

How to Apply

Please complete the application posted on this website: