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PhD Position in Machine Learning Potentials, Res ... (No replies)
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PhD Position in Machine Learning Potentials, Research Alliance Ruhr, Germany
A fully funded PhD position (3 years) with a focus on the development of modern machine learning potentials for atomistic simulations is immediately available in the group of Prof. Jörg Behler, Chair for Theoretical Chemistry II, Ruhr-Universität Bochum, Germany.
The position is a joint position co-supervised by Prof. Jörg Behler (Research Center Chemical Sciences and Sustainability, http://www.theochem2.ruhr-uni-bochum.de) and the Research Center Trustworthy Data Science and Security at TU Dortmund. Both research centers are part of the newly established Research Alliance Ruhr, a joint initiative of TU Dortmund, Ruhr-Universität Bochum and Universität Duisburg-Essen funded by the state of North Rhine-Westphalia to further expand the research landscape in the metropolitan area Ruhr. Our group is situated very close to the RUB-Campus in Bochum. We offer an exciting international research environment and excellent working conditions with state-of-the-art equipment and high-performance computing facilities.
As a very interdisciplinary team we are working at the frontier between chemistry, physics and materials science performing atomistic simulations of complex systems. Our central interests are chemical processes at interfaces (e.g. electrochemistry and catalysis) and reactions in solution. To study these topics, we develop modern machine learning potentials, which combine the accuracy of quantum mechanical electronic structure methods and the efficiency of classical force fields. With these tools we can perform molecular dynamics simulations of large systems on long time scales to understand in detail mechanisms and properties at the atomic scale. Our group is among the world-leading groups in the field of machine learning potentials, and in the past two decades we have substantially contributed to the progress in this field. The advertised project has a very strong focus on methodical developments in the field of machine learning and data analysis, and candidates should be highly interested in both, code development as well as applications in chemistry and materials science.
The successful candidate should have a MSc in chemistry, physics, materials science, computer science, engineering or a related field and very good communication skills in English (oral and writing). The ideal candidate will have some knowledge about electronic structure calculations (preferably density functional theory), atomistic simulation techniques like molecular dynamics or Monte Carlo, and strong programming skills in Python and/or Fortran.
Further information on the application process, which is handled by TU Dortmund, can be found at:
https://rc-trust.ai/Open-PhD-Positions-RC-Trust.pdf
If you are interested in the positions, please send your application (including Reference-No.w14-23) until 31th May 2023 to:
Research Center Trustworthy Data Science and Security
Technische Universität Dortmund
Prof. Dr. Emmanuel Müller
Joseph-von-Fraunhofer-Str. 25
44227 Dortmund
Please send the usual documents (motivation letter, CV, copies of your transcripts and language certificates as well as a description of your programming skills) as single pdf by email to [email protected]. Please mention in your cover letter that you are interested in the project on machine learning potentials in collaboration with the Behler group.