210 affective-computing-"https:" "https:" "https:" "UCL" positions at Technical University of Munich
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26.03.2026, Academic staff Doctoral Candidate f/m/d in computational proteomics/bioinformatics with a focus on plant proteomics Candidates must hold a master´s degree in Data Engineering, Data
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knowledge of the German language besides English. If interested, please send your full application to the email adress provided below. At the Mechanics & High Performance Computing Group, there is an open
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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
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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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Informatics Initiative (MII)/FHIR standards Design and implement methodological concepts and software for benchmarking frameworks for AI evaluation Independently develop and implement research ideas within
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Europe • Membership in the International Graduate School of Science and Engineering (IGSSE) and participation in the course program (https://www.igsse.gs.tum.de/en/igsse/about/) • IGSSE-funded doctoral
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07.08.2025, Academic staff The Chair of Computational Mathematics at the Technical University of Munich (TUM) invites applications for one PhD position. The Chair of Computational Mathematics
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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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University of São Paulo, Brazil. This position focuses on developing advanced computer vision methods and hardware setup for detecting and predicting plant diseases in soybean cultivation. About Us The Chair
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microgrid setup that combines green hydrogen production, fuel cells, and multi-level battery storage. - Analyze and evaluate operational data to precisely quantify the system’s environmental impact using