205 computer "https:" "https:" "https:" "https:" "UCL" positions at Technical University of Munich in Germany
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07.04.2026, Academic staff PhD position at the interface of computational physics, machine learning, and experimental reactor design. The project focuses on developing PINN-based simulations
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using the model iLand. The work is embedded in the BETA-FOR project (https://www.uni-wuerzburg.de/for5375/) and will collaborate closely with the Forest Economics and Sustainable Land-use Planning group
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07.04.2026, Academic staff The Chair of Renewable and Sustainable Energy Systems at TUM is seeking a research assistant (up to TV-L E13, fixed-term) with the opportunity to pursue a Ph.D. The focus is on energy modeling, data-driven planning approaches, and the development of innovative data...
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requires experience in cognitive processes underlying food choice, context effects, experimental research, quantitative analysis, computational modeling, and eye tracking. Applications must be submitted by
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excitations and excitonic effects using advanced Wannier-based methods * Quantum transport in polymer materials with electron–phonon coupling Full details and application instructions: https://www.ch.nat.tum.de
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and publications, there is the possibility of international research stays and conference travel. Benefit from a comprehensive training program covering both subject-specific and interdisciplinary
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: A master’s degree in Operations Research, Applied Mathematics, Computer Science, Industrial Engineering, or a related field A solid background in dynamic programming, Markov decision processes
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application, you confirm that you have acknowledged the above data protection information of TUM. Kontakt: adrian.doerfler@tum.de More Information http://www.mos.ed.tum.de/nma
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application, you confirm that you have acknowledged the above data protection information of TUM. Kontakt: contact.btd@ls.tum.de More Information https://www.lse.ls.tum.de/btd/home/
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/11250664 https://www.jmlr.org/papers/v26/25-1161.html Job Specifications For PhD applicants: Excellent Master’s degree (or equivalent) in engineering, computer science, or related disciplines (typically