Postdoctoral and PhD positions are available to work on combining density functional theory calculations and machine learning (ML) for the high-throughput screening of hybrid organic-inorganic halide perovskites as part of an Air Force Office of Scientific Research funded effort. A particular focus will be on assessing the reliability of the ML predictions (Sutton et al., Nat. Commun. 2020, 11, 4428).

The work will be carried out in Christopher Sutton’s group at the University of South Carolina and will be performed in close collaboration with Gabor Csanyi at the University of Cambridge, with the potential for travel once restrictions are eased.

The successful postdoctoral candidate will hold a Ph.D. in Materials Science, Physics, Chemistry, or a related discipline and have experience in scientific programming, atomistic simulations and/or ML. Excellent oral and written communication skills and the ability to work well in a collaborative research environment are essential.

The initial postdoctoral appointment will be for one year and can be renewed up to three years subject to satisfactory performance. Interested candidates should send a brief cover letter, CV, and contact information of two references as a single PDF file to: [email protected]