Ph.D. position in Machine Learning for Molecular Simulations

Published
Closing Date
WorkplaceMünchen, Bayern, Germany
Category
Position
MyTUM-Portal
Technische Universität München

02.10.2024, Wissenschaftliches Personal

The successful applicant will work on molecular dynamics simulations, where molecular interactions are predicted by neural network potentials. These state-of-the-art neural network models promise simulations at unprecedented accuracy, giving quantitative insight into physical processes at the nanoscale. The candidate will develop the next generation of neural network potentials and apply them to problems from different scientific fields ranging from life sciences to engineering. For more information, visit our webpage ?url=www.epc.ed.tum.de%2Fen%2Fmfm&module=jobs&id=201034" target="_blank" rel="nofollow">?url=www.epc.ed.tum.de%2Fen%2Fmfm&module=jobs&id=201034" target="_blank" rel="nofollow">www.epc.ed.tum.de/en/mfm.

Your profile ï‚Ÿ M.Sc. degree in informatics, physics, chemistry, or engineering (candidates that will soon obtain the degree are also welcome to apply)
ï‚Ÿ strong background in machine learning
ï‚Ÿ proficiency in programming (especially Python) ï‚Ÿ experience with molecular simulations and knowledge of statistical physics is beneficial ï‚Ÿ fluent in spoken and written English (knowledge of German is beneficial but not required) Our offer You will join a young research group working on state-of-the-art research in molecular modeling and become part of TUM, a top European university. The position is available immediately and for a duration of three years (possible extension). Salary is based on the Free State of Bavaria public service wage agreement (100%, TV-L E13). Additional funding is available for scientific equipment and conference travel expenses.

How to apply?
Please send your application by e-mail to info.mmfmmw.tum.de with the subject -PhD Application-. The application should include (in one single PDF document) a cover letter stating your motivation and back-ground for applying for the position in our group, a CV, certificates, transcript of grades, and contact information of two references. Applications will be reviewed on a rolling basis until the position is filled. Preference will be given to applications received before the 1st of December 2024.

For any questions, please do not hesitate to contact Prof. Dr. Julija Zavadlav (info.mmfmmw.tum.de).

Contact Technical University of Munich Multiscale Modeling of Fluid Materials (Prof. Julija Zavadlav) Boltzmannstr. 15, 85748 Garching b. München
?url=www.epc.ed.tum.de%2Fen%2Fmfm&module=jobs&id=201034" target="_blank" rel="nofollow">?url=www.epc.ed.tum.de%2Fen%2Fmfm&module=jobs&id=201034" target="_blank" rel="nofollow">www.epc.ed.tum.de/en/mfm.

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Kontakt: info.mmfmmw.tum.de

Mehr Information

?url=http%3A%2F%2Fwww.epc.ed.tum.de%2Fen%2Fmfm&module=jobs&id=201034" target="_blank" rel="nofollow">?url=http%3A%2F%2Fwww.epc.ed.tum.de%2Fen%2Fmfm&module=jobs&id=201034" target="_blank" rel="nofollow">www.epc.ed.tum.de/en/mfm
In your application, please refer to myScience.de and reference JobID 201034.


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