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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

Bewerbungsende: 04.01.2021

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.

Job description:
- 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

Requirements:
Completed master’s degree in mathematics, physics, computer science, chemistry or related disciplines

Desirable:
- 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 (jan.hermann@fu-berlin.de).

Stellenauschreibung vom: 06.12.2020