Fachbereich Mathematik und Informatik - Institut für Mathematik BIFOLD
Researcher (m/f/d) Full-time job Limited to 31.12.2022 Entgeltgruppe 13 TV-L FU Reference code: BIFOLD-2020-3
The newly established BIFOLD-funded research group “Machine Learning for Materials Science” is focused on developing and integrating machine learning techniques into computational methods in electronic structure theory. We are looking for a coworker on the topic of incorporating machine learning into density functional theory with the goal of making existing approximations more accurate. Familiarity with computational chemistry would be an advantage. Applications from candidates with a doctoral degree are welcome.
- Hold a key role in the methodological developments and subsequent applications of the project
- Present the results of the project at (virtual) conferences and hold a key role in manuscript preparation
Completed master’s degree in mathematics, physics, computer science, chemistry or related disciplines
- Ability to semi-independently handle a research project
- Experience with the use of deep learning in natural sciences
- Working knowledge of density functional theory
- Good general programming skills, in Python in particular
- Excellent English skills
For further information, please contact Herr Dr. Jan Hermann (email@example.com).
Stellenauschreibung vom: 06.12.2020