25.03.2024, Wissenschaftliches Personal
We are searching for motivated personnell (PhD, postdoc) with mathematics or informatics background. You will be working in the FAIRmat project (a NFDI consortium), where we build a FAIR data infrastructure for condensed matter physics and chemical physics of solid bodies, useable by materials science groups in Germany. As postdoctoral researcher, you will also be able to work on machine learning method development.
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 one motivated researcher to hire as a doctoral or postdoctoral researcher at TUM. You will be collaborating with the research group of Prof. Dr. Felix Dietrich, at the chair of Scientific Computing in Computer Science of TUM.
Remuneration is 100% TVL E14 according to the German public sector rates, as long as all conditions are met (otherwise TVL E13).
You will be involved in the project FAIRmat (an NFDI consortium).
FAIRmat is building a FAIR data infrastructure for condensed-matter physics and the chemical physics of solids for materials science groups all over Germany (and world-wide). In FAIRmat, we develop the NOMAD software with many other collaborators in Germany. NOMAD is the main collaboration tool in the project, where scientists can upload their data in a standardized way, making them FAIR (Findable, Accessible, Interoperable, Reproducible - but also Fully AI Ready!).
Your role in the project will be in the team of developers (about 10 people), working on the open source software NOMAD .
As a postdoctoral researcher, you will also be involved in research on method development for machine learning algorithms and advise PhD candidates (see the homepage for potential research directions).
Requirements
- Doctorate (PhD) in Informatics, Mathematics, or related. You can also apply if you do not have a PhD, but only with significant (ideally: industry) experience with python software development.
- Good knowledge about Python software development (you will contribute to NOMAD).
- Ideally: knowledge / background in machine learning method development.
- 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: FAIRmat" to [email protected] (deadline: 21.04.2024 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 in the group from Prof. Dietrich, why at TUM? Why do you want to work on NOMAD?
- CV including PhD topic description, publications, academic education, (optional) industry experience, and (optional) completed projects.
- 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
[email protected]
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 [email protected]
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