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offer A vibrant research community in an open, diverse and international work environment Scientific excellence and extensive professional networking opportunities A structured PhD program with a
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profile An excellent university degree (Master's, Diploma, or equivalent) in Computer Science or a related technical field (e.g., Interactive Media Systems, Virtual Reality Development, Software Engineering
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in computer science, data science, and research IT. The overarching goal is to jointly develop sustainable, FAIR-compliant data structures that will support scientific discovery within the cluster in
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Mechanical Engineering, Computer Science, Mechatronics or a comparable subject Solid background in programming (e.g., Python or C++) is essential Experience with machining processes or ML approaches
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Student Assistant (m/f/d) | "The Art of AI. Rethinking Notions of Creativity, Aesthetics and Ethics"
Kunsthistorisches Institut in Florenz - Max Planck Institute, Florence, Italy | Germany | about 2 months agohistory, philosophy and computer science and engages with questions that range from historical narratives of automata and robots to contemporary challenges such as deep-fakes, AI-assisted artistic
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computing and quantum computing are future-oriented topics that our researchers are working on. Our research fields are in the following areas - Fraunhofer ITWM »Optimization« »Processes and materials
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ideas from the lab to real-life applications, improving lives. Helmholtz Munich invites outstanding early-career researchers (f/m/x) to apply for the Health AI Fellows (HAIF) Program , a unique
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programme, which includes tailor-made training courses, workshops, retreats and conference trips. You will have access to state-of-the-art laboratories and theoretical methods, individual supervision, and a
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plasma cells within specific regions of the bone marrow. Requirements and Skills: Excellent M.Sc. degree (or equivalent) in the areas biomedical, computational or nutritional sciences A background in
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software (e.g., LLM agents for finding and fixing bugs) Static and dynamic program analysis (e.g., to infer specifications) Test input generation (e.g., to compare the behavior of old and new code via