-
optimiser that accelerates both workflow efficiency and materials discovery. Main Tasks and responsibilities: AI4LSQUANT aims to accelerate quantum modelling by learning fast, accurate surrogates
-
familiarity with at least one of: DFT workflows, Wannier/TB model building, or quantum-transport simulations; willingness to become hands-on across the stack. Comfortable with Linux/HPC, job schedulers, and
-
their characterization under different working conditions. Specifically, the researcher will focus on (1) development of clean room protocols for TENG fabrication, (2) morphological and electrical
Searches related to morphological modeling
Enter an email to receive alerts for morphological-modeling positions