75 assistant-professor-computer-science-data "https:" PhD positions at Technical University of Munich
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with a focus in economics, or related disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high
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access to cutting-edge infrastructure, interdisciplinary collaborations, and an active PhD network spanning multiple institutions in the Munich area • More information: https://syb.cs.tum.de , https://hn
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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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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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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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with their environment. We use an interdisciplinary approach from protein biochemistry to cell biology to analyze the machinery and mechanisms that monitor cellular protein biogenesis. THE PROJECT
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teaches with approximately 25 staff members in the Department of Mechanical Engineering at the School of Engineering and Design (SoED) of the Technical University of Munich (TUM) in Garching on the design
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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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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