Postdoc in Machine Learned Semiconductor Material Properties for Quantum Transport Simulations

Postdoc in Machine Learned Semiconductor Material Properties for Quantum Transport Simulations

The simulation of electronic devices has a long and successful history of accompanying experimental developments, be it for transistors or memory cells. Nowadays, to be of practical relevance, such technology computer aided design (TCAD) tools should operate at the ab-initio and quantum mechanical level. Moreover, they should capture the interplay between electrical (voltage-induced currents), thermal (excitation of crystal vibrations), and structural (migration of atoms) effects with an atomistic resolution. This can be achieved by self-consistently coupling molecular dynamics (MD), density-functional theory (DFT), and quantum transport (QT) simulations of both electrons and phonons.

The Computational Nanoelectronics Group of ETH Zurich recently started implementing a novel, state-of-the-art TCAD tool called QuaTrEx that can perform ab-initio QT calculations at unprec...