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PostDoc positions in physics-enhanced machine learning (m/f/d)

21.06.2024, Wissenschaftliches Personal

We are searching for two motivated researchers (postdocs) with a mathematics or informatics background. You will be working in the group of Prof. Felix Dietrich on methods for physics-enhanced machine learning.

About Us
Located in the prosperous capital of Bavaria and home to over 40000 students, the Technical University of Munich (TUM) is one of the world's top universities. It is committed to excellence in research and teaching, interdisciplinary education, and the active promotion of promising young scientists. TUM benefits from the healthy mix of companies and startups of all sizes headquartered in the region and is tightly connected to regional research hospitals. The university also forges strong links with companies and scientific institutions across the world.


Description
We are looking for two motivated persons to hire as a postdoctoral researchers at TUM. Remuneration is 100% TVL E14 (postdoc position), according to the German public sector rates, as long as all conditions are met.

You will be collaborating with the research group "Physics-Enhanced Machine Learning" of Prof. Dr. Felix Dietrich at TUM. We are proud to be a very international group with gender parity with currently one postdoc (F) and six PhD candidates (3F, 3M). As a postdoctoral researcher, you will be working on machine learning algorithms to understand physical systems better, and use inspiration from knowledge-based approaches to improve general machine learning algorithms. You also have to help advise PhD candidates. You can apply for the SOFTWARE or the MATHEMATICS position (or both). Depending on your skill set, you can work on topics revolving around machine learning in computer science including software development, or on topics related to the underlying theory and mathematics of machine learning algorithms. See the homepage for potential research directions, recent software, and Google scholar for recent papers.

Requirements (SOFTWARE position)

  • Doctorate (PhD) in Informatics, Mathematics, or related.
  • Knowledge about Python software development.
  • Knowledge in machine learning method development.
  • Optional, ideal: Knowledge in scientific computing (computational fluid dynamics, solving linear systems, high-performance computing, etc.).
  • Soft skills: analytical thinking, structured and organized work, high intrinsic motivation.
  • For E14: leadership experience (supervising PhD students or Master students).
Requirements (MATHEMATICS position)
  • Doctorate (PhD) in Informatics, Mathematics, or related.
  • Knowledge about harmonic analysis, functional analysis, and/or numerical analysis.
  • Knowledge in the analysis of machine learning methods.
  • Optional, ideal: Knowledge in scientific computing (computational fluid dynamics, solving linear systems, high-performance computing, etc.).
  • Soft skills: analytical thinking, structured and organized work, high intrinsic motivation.
  • For E14: leadership experience (supervising PhD students or Master students).


How to apply?
Send your application with subject "Postdoc position: PhysML" to phdapplications@mailsccs.in.tum.de (deadline: 15.07.2024 EOD), and attach the following (all in one PDF):
  • Up to one page of motivation letter: Why do you want to work as a postdoc, why in machine learning, why MATH/SOFTWARE, why in the group from Prof. Dietrich, why at TUM?
  • CV including PhD topic description, publications, academic education, (optional) industry experience, (optional) grants / funding experience.
  • Transcript of records (completed courses and grades) from your Masters.
  • Names of one or two contact persons (we may ask them for letters of reference).


Note that TUM has been pursuing the strategic goal of substantially increasing the diversity of its staff. As an equal opportunity and affirmative action employer, TUM explicitly encourages nominations of and applications from women as well as from all others who would bring additional diversity dimensions to the university's research and teaching strategies. Preference will be given to disabled candidates with equal qualifications. International candidates are also highly encouraged to apply.

Contact
If you have any questions about the application or the project, write an email or use the contact form on the website:

Prof. Dr. Felix Dietrich
phdapplications@mailsccs.in.tum.de
www.fd-research.com/contact
Link to the TUM page of Prof. Dietrich

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. Felix Dietrich