Job Description

The Rosen Research Group at Princeton University (https://rosen.cbe.princeton.edu) is searching for a postdoctoral or more senior researcher interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials. Candidates who are nearing completion of their Ph.D. (i.e. with a confirmed defense/viva date) or hold a Ph.D. in chemical engineering, materials science and engineering, chemistry, physics, or a closely related field are particularly encouraged to apply.

We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular dynamics, and materials chemistry. Strong Python programming skills are required, and prior experience with developing open-source software or databases will be considered a plus. Candidates should apply at: https://www.princeton.edu/acad-positions/position/38801. Please include a cover letter, research statement (a discussion of past research, expertise, and research interests) and contact information for three references.

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.

Princeton University is an Equal Opportunity/ Affirmative Action Employer, and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law.