Ph.D. position in Machine Learning-Powered Molecular Simulations

Updated: about 10 hours ago

09.05.2024, Wissenschaftliches Personal

The Multiscale Modeling of Fluid Materials group is looking for talented and ambitious scientists interested in unique interdisciplinary research, integrating machine learning, molecular simulations, statistical physics, multiscale modeling, and uncertainty quantification.

In particular, openings are available in connection with the following projects:
- Developing a novel computational framework to discover rational design rules of peptide-based materials used in emerging technologies ranging from drug delivery to soft semiconductor devices.
- Advancing material design for modern additive manufacturing techniques, such as laser powder bed fusion, with state-of-the-art simulations, enabling accurate alloy microstructure prediction.

For more information, visit our webpage www.epc.ed.tum.de/en/mfm.

Your profile
- M.Sc. degree in physics, chemistry, computer science, or engineering (candidates that will soon obtain the degree are also welcome to apply)
- strong background in molecular simulations and/or machine learning
- proficiency in programming (especially Python)
- fluent in spoken and written English (knowledge of German is beneficial but not required)

Our offer
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 [email protected] with the subject “PhD Application”. The application should include (in one single PDF document): a cover letter stating your motivation and background for applying for the position in our group, CV, certificates, transcript of grades, and contact information of two references. Applications will be reviewed on a rolling basis until the position is filled.

For any questions, please do not hesitate to contact Prof. Dr. Julija Zavadlav ([email protected]).


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: Prof. Dr. Julija Zavadlav; [email protected]


More Information

http://www.epc.ed.tum.de/en/mfm



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