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-edge Machine Learning applications on the Exascale computer JUPITER. Your work will include: Developing, implementing, and refining ML techniques suited for the largest scale Parallelizing model training
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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
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Max Planck Institute for Intelligent Systems, Tübingen site, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | 4 days ago
, virtual reality, biology and medicine. Using unique 3D & 4D capture facilities, machine learning, computer vision and advanced graphics, we are modeling humans and animals shape and behavior. In the Eye
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01.10.2025, Wissenschaftliches Personal This PhD position is part of the interdisciplinary TUM GNI project AUROrA – AI-Driven Urban Flood Resilience: Integrating Earth Observation and Architectural
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24.09.2025, Wissenschaftliches Personal The Chair for Efficient Algorithms, led by Prof. Stephen Kobourov, invites applications for a fully funded PhD position at the Technical University of Munich
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PhD Positions Country Germany Application Deadline 19 Oct 2025 - 23:59 (Europe/Berlin) Type of Contract Temporary Job Status Part-time Hours Per Week 30 Offer Starting Date 1 Jan 2026 Is the job funded
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improve the sustainability, the energy efficiency and the safety of industrial processes. The Department of Electrochemical Systems is looking for a PhD Student (f/m/d) for fuel cell electrode test. The
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can be found on our website . Tuition fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree / double degree programme No Description/content IMPRS-ML – A Structured PhD
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Institute for Molecular Imaging. The primary objective of the group’s research is to examine the function of immune cells in response to inflammatory processes in living organisms by employing innovative
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methods to make them usable for transparent energy systems analyses. The collected data will be processed and semantically enriched using methods you develop before being transferred to a knowledge graph