42 assistant-professor-computer-science-data-"https:"-"https:"-"https:"-"https:"-"UCL" PhD positions at Technical University of Munich
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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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12.01.2026, Academic staff The Professorship of Machine Learning at the Department of Computer Engineering at TUM has an open position for a doctoral researcher (TV-L E13 100%; initial contract 1.5
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details of two referees The deadline for application is March 1st, 2026. For more information about PFT group, please check on our website Particle and Fiber Technology The position is suitable for disabled
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spectroscopy technologies (i.e. optical hardware). • Molecular biology / protein biochemistry expertise. • Experience in analyzing protein structural data (not necessarily acquiring the data). • Having already
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, environmental economics, agricultural sciences with a focus in economics, or related disciplines - strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics
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. Our teaching and research focus lies on computer-based development of engineering products, particularly on the planning and realization of built facilities using computational modeling and simulation
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for Preventing Stomach Cancer 18.03.2026 150 Years of Electrical and Computer Engineering at TUM 17.03.2026 Living material makes harmful UV-light visible 17.03.2026 Urban trees can absorb more CO₂ than cars emit
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application, you confirm that you have acknowledged the above data protection information of TUM. Kontakt: thesis.mhpc@ed.tum.de More Information https://www.epc.ed.tum.de/mhpc
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Master’s degree in physics, chemistry, materials science, chemical engineering, or a related field who are excited about applying machine learning and data science to real-world materials challenges
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Science. The PhD positions will be at the intersection of Data Science and Social Sciences and will focus on topics such as Explainable & Fair AI, AI Auditing, AI Alignment, and AI Safety in general. We