Ph.D. students (f/m/d) in Physics-based Machine Learning

Technische Universität München
March 04, 2023
Offerd Salary:Negotiation
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Contract Type:Other
Working Time:Negotigation
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Ph.D. students (f/m/d) in Physics-based Machine Learning

20.01.2023, Wissenschaftliches Personal

The Professorship for Multiscale Modeling of Fluid Materials at TUM Campus Garching is looking for two Ph.D. students (f/m/d) in Physics-based Machine Learning, 100% with starting date in April 2023.

Scientific environment

The Multiscale Modeling of Fluid Materials group provides a unique interdisciplinary environment, integrating state-of-the-art machine learning, multiscale simulations, and statistical physics to understand and exploit soft matter systems. The group, led by Prof. Julija Zavadlav, is part of the School of Engineering and Design at one of Europe's top universities, the Technical University of Munich. For more information, visit www.

Project description

The positions are offered in the context of an ERC Starting Grant project called ‘SupraModel: Peptide-based Su-pramolecular Co-assembly Design: Multiscale Machine Learning Modeling Approach.' ERC Starting Grant is a highly competitive funding program by the European Research Council (ERC) to support ground-breaking research in Europe.

SupraModel proposes a novel computational framework that will enable a rational design of peptide-based mate-rials used in emerging technologies ranging from drug delivery to soft semiconductor devices. The successful ap- plicant will work with other project members to develop next-generation molecular models where deep neural networks predict molecular interactions. These models enable molecular simulations at an unprecedented accuracy, giving quantitative insight into physical processes at the nanoscale, and will be used to advance supramolecular peptide-based materials.

Your profile

The position is open to candidates holding (or who will hold) a M.Sc. degree in physics, chemistry, applied mathe-matics, or related fields. We are particularly interested in applicants with:

  • experience with machine learning and basic knowledge of statistical mechanics/physics
  • proficiency in Python programming
  • fluent in spoken and written English(knowledge of German is not required)
  • strong motivation and commitment to scientific excellence
  • Our offer

    Join our young research group with a scientifically stimulating atmosphere and participate in cutting-edge physics-aware machine learning research! The position is available for three years, with an expected starting date of April 2023. Salary is based on the Free State of Bavaria public service wage agreement (100%, TV-L E13, starting at a higher level 2). Additional funding is available for scientific equipment and conference travel expenses.

    How to apply?

    Please send your application or questions regarding the position by e-mail to [email protected] The ap-plication should include (in one single PDF document): a cover letter stating your motivation and background for applying for this Ph.D. position, a CV, certificates, transcript of grades, and contact information of two references.

    TUM is an equal opportunity employer. TUM aims to increase the proportion of women, therefore, we particularly encourage applications from women. Applicants with severe disabilities will be given priority consideration given comparable qualifications. Data Protection Information: As part of your application for a position at the Technical University of Munich (TUM), you submit personal data.
    Please note our privacy policy in accordance with Art. 13 General Data Protection Regulation (DSGVO) https:// for the collection and processing of personal data in the context of your application. By submitting your application, you confirm that you have read the privacy notice of TUM.

    Hinweis zum Datenschutz: Im Rahmen Ihrer Bewerbung um eine Stelle an der Technischen Universität München (TUM) übermitteln Sie personenbezogene Daten. Beachten Sie bitte hierzu unsere Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. Durch die Übermittlung Ihrer Bewerbung bestätigen Sie, dass Sie die Datenschutzhinweise der TUM zur Kenntnis genommen haben.

    Kontakt: [email protected]

    Mehr Information

    PhDERCSupraModel PhDERCSupraModel, (Type: application/pdf, Größe: 357.1 kB) Datei speichern

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