The Rosen Research Group at Princeton University (https://rosen.cbe.princeton.edu) is searching for a postdoctoral researcher interested in computational materials science, particularly building upon recent developments in the area of machine learning interatomic potentials. The successful candidate will leverage and augment machine learning interatomic potentials to better address the complexities of real materials that are often neglected in traditional first-principles simulations. Expertise with density functional theory, molecular dynamics, AI model development, free energy predictions, and/or enhanced sampling methods applied to solid-state materials is desirable. Applicants must have (or expect to have at time of appointment) a Ph.D. in chemical engineering, materials science, physics, chemistry, or a closely related field are particularly encouraged to apply.

This position is not eligible for sponsorship of an H-1B visa requiring consular processing; other visa sponsorships (including H-1B visas not requiring consular processing) may be available, as appropriate.

This position is for one year with the possibility of renewal pending satisfactory performance and continued funding.  The work location for this position is in-person on campus at Princeton University. 

This position is subject to the University's background check policy.

Candidates should include a cover letter, CV (including a list of publications), research statement (a discussion of past research, expertise, and research interests), and three confidential letters of referral.