Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
will work with future emerging topics in High Energy Particle Physics and Quantum Physics. The aim of the research is to develop the underlying theory, simulations and Artificial Intelligence (AI
-
important - Prior experience with density functional theory or machine learning is desirable - Proficiency in the Python programming language is important, as well as Fortran - Strong written and oral
-
of materials. The position requires extensive knowledge in performing quantum mechanical calculations (e.g., first principles density functional theory (DFT)) to elucidate complex reaction mechanisms occurring
-
Physics, or a related discipline. Experience with recognized computational chemistry software (e.g., Gaussian, Dalton, TurboMole) is highly desirable. Experience in Time-Dependent Density Functional Theory
-
. In this project, we aim to develop digital tools combining density functional theory (DFT) and machine learning (ML) to accelerate the in-silico design of solid catalysts for the DA process. - Perform
-
-Performance Computing Advanced Know-How in the fields of HPC Scientific Domain Expertise: While the position is open to various backgrounds, proven expertise in molecular simulation and density functional
-
Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | 22 days ago
(Master/Diploma) in the field of Chemistry, Physics, Computer Science or related field # Knowledge of Density Functional Theory (DFT) # Familiarity with artificial intelligence methods # Good knowledge
-
, spanning from the investigation of surface plasmons and the design of nano-structured catalyst materials to density functional theory calculations to understand surface reactions and materials on an atomic
-
in structure characterization of homogeneous and heterogeneous catalysts using nuclear magnetic resonance (NMR) spectroscopy and density functional theory (DFT) to deduce structure-property
-
systems at various scales, for example using ab initio electronic structure methods like density-functional theory, developing interatomic potentials with various methodologies including machine learning