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abilities into the long-term development of the professorship. Ideally, you are already knowledge-able in the fields of life cycle assessment, simulation, mathematical optimization, and / or material flow
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qualifications and requirements university degree (Diploma/Master) in electrical or electronic engineering, telecommunications engineering, computer science, physics, mathematics, or equivalent strong programming
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Engineering, Mathematics, Statistics, or related fields. • Strong programming skills in Python, Java, C++, etc. • A solid foundation in generative AI, machine learning, and related areas. • An Interest in eye
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Panny in the Department of Mathematics, within the TUM School of Computation, Information and Technology, located at the Garching campus. The group was established in 2023 and primarily focuses
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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
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good publication track record Above-average master’s degree in computer science, electrical/ mechanical engineering, applied mathematics, or a similar engineering-oriented quantitative discipline
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Python) M.Sc. in Computer Science, Physics or Mathematics or a similar subject area We encourage you to apply even if your profile does not meet all of the requirements for the role yet. Your profile is
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06.05.2024, Wissenschaftliches Personal The Leibniz Institute for Food Systems Biology at the Technical University of Munich (Leibniz- LSB@TUM) is a research institution of the Leibniz Association looking for a Postdoctoral Scientist (m/f/d) in the research group Mechanoreceptors/ Section II to...
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resilience. Undertake comprehensive data analysis and develop sophisticated mathematical models for simulating power system behaviors under various scenarios. Development and Testing: Design and develop
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productivity, driver shortages, safety, and environmental friendliness. A major obstacle towards this promising future is to guarantee in a mathematically provable way that the automated system always works