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Field
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. Publish and present findings in international journals and conferences. Supervise and mentor junior researchers and students. Profile PhD in Computer Science, Biomedical Engineering, Data Science, or a
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influenced corrosion (MIC) in marine environments. It uses AI-supported models, Bayesian data fusion, and real-time sensor data integration. Your responsibilities include: Development of a digital twin (DT
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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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writing. Drive the publication of research results in top-tier robotics conferences and journals. Requirements Ph.D. in Robotics, Mechanical Engineering, Electrical Engineering, Computer Engineering, or a
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Garching campus. TUM’s Department of Computer Science is part of the TUM School of Computation, Information and Technology (CIT). Employment Conditions • Start date: Flexible, from January 2026 onward
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advanced machine learning methods for multimodal and 3D medical image analysis in musculoskeletal medicine, in close collaboration with clinicians and computer scientists. PhD or Postdoctoral Researcher
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Max-Planck-Institut für Kohlenforschung, Mülheim an der Ruhr | M lheim an der Ruhr, Nordrhein Westfalen | Germany | 33 minutes ago
November 15th 2025 for full consideration. Late applications may still be reviewed depending on circumstances. Shortlisted candidates will be notified within three weeks of submission. More information about
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persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance. Data Protection Information: When you apply for a position with the
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. Depending on your profile, you can set your own focus (e.g. on scalable training, data/feature pipelines, or model development) working closely with Helmholtz Munich, MDC Berlin, and NVIDIA. You will: Set up
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or empirical research including statistical data analysis. The position is associated with the project “Probabilistic Reasoning about Common Ground” under the auspices of the Collaborative Research Center