208 computer-programmer-"https:"-"Inserm"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" positions at Technical University of Munich
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04.12.2025, Wissenschaftliches Personal We are looking for an Independent junior research group leader (m/f/d) with knowledge of data / AI science to set up and lead the AI Core Unit of the BioSysteM Cluster of Excellence as soon as possible. The position is initially for 4 years and can be...
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22.12.2025, Wissenschaftliches Personal We are an interdisciplinary team at the Chair of Safety, Performance and Reliability for Learning Systems, and we are looking for exceptional postdoctoral researchers to join our team. The postdoctoral positions will be full-time (100%, TV-L E13). We are...
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good PhD or master´s degree in industrial engineering, process engineering, chemistry, computer science or similar disciplines. You think analytically, work solution orientated and voluntarily in
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, Human-Computer Interaction, and their responsible applications. Ideal candidates will have: An M.Sc. degree (or equivalent) in Computer Science, Game Engineering, Mathematics, Statistics, or related
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junior research group leader with a focus on data and AI Science to join us as soon as possible. Your qualifications PhD in Computer Science, Mathematics, Physics or related fields Experience in applied
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prestigious Humboldt Research Fellowships for the Logistics and Supply Chain Management research group at TUM School of Management. With the scouting program, the foundation aims to attract highly talented
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degree or PhD in Computer Science, Electrical Engineering, Control Systems, or a closely related field. Experience in reachability analysis, formal verification/model checking, control theory, or related
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Germany for more than 12 months in the 36 months immediately before the recruitment date. Nationality: Open to all nationalities. Doctoral Programme Enrolment: You must be willing to enrol in a doctoral
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of Orthopaedics and Sports Orthopaedics and the Institute for AI and Informatics in Medicine. We work at the intersection of artificial intelligence, medical imaging, and clinical practice, developing methods
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the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission analysis, and infrared thermography