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Ph.D. position in Machine Learning for Molecular Simulations
02.10.2024, Wissenschaftliches Personal
The Multiscale Modeling of Fluid Materials group at the Technical University of Munich is looking for talented and ambitious scientists interested in unique interdisciplinary research, integrating molecular simulations, machine learning, statistical physics, multiscale modeling, and uncertainty quantification.
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 www.epc.ed.tum.de/en/mfm.
Your profile
M.Sc. degree in informatics, physics, chemistry, or engineering (candidates that will soon obtain the degree are also welcome to apply)
strong background in machine learning
proficiency in programming (especially Python)
experience with molecular simulations and knowledge of statistical physics is beneficial
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.mmfm@mw.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.mmfm@mw.tum.de).
Contact
Technical University of Munich
Multiscale Modeling of Fluid Materials (Prof. Julija Zavadlav)
Boltzmannstr. 15, 85748 Garching b. München
www.epc.ed.tum.de/en/mfm.
The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance.
Data Protection Information:
When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.
Kontakt: info.mmfm@mw.tum.de
More Information
http://www.epc.ed.tum.de/en/mfm
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