Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
biophysics/chemistry/physics and related fields Experience with Molecular Dynamics using coarse grained or atomistic models Advantage is experience with simulations of disordered proteins/polymers and
-
) Requirements for candidate: MSc in computational biophysics/chemistry/physics and related fields Experience with Molecular Dynamics using coarse grained or atomistic models Advantage is experience with
-
computational methodologies, ranging from atomistic and electronic-structure–based materials modeling and characterization, via machine-learning and high-throughput methods, to ab initio calculation
-
and Simulation Group at ICN2 conducts cutting-edge research in computational materials science, focusing on electronic structure methods, atomistic simulations, and multiscale modelling. The group
-
, particularly machine-learned interatomic potentials, in the context of chemical research. Knowledge of atomistic and coarse-grained classical force fields. Experience creating and maintaining scientific software
-
) with DFT atomistic simulations to investigate the electronic structure and defect states in wide bandgap semiconductor nanomaterials. The goal is to better understand and optimize function
-
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
-
effects on the particle and sub-particle level into hierarchical pseudo-2D descriptions of batteries Link continuum descriptions to quantum computing accelerated atomistic approaches in an interdisciplinary
-
practices. Preferred Knowledge, Skills, and Abilities: You have experience with electronic-structure or atomistic simulation workflows (e.g., VASP, Quantum ESPRESSO) and associated Python tools such as ASE
-
different types of simulations at different scales. For the atomic level, you will use atomistic molecular dynamics simulations, which are so expensive computationally that supercomputers are needed