170 parallel-computing-numerical-methods positions at Technical University of Munich in Germany
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18.09.2024, Wissenschaftliches Personal We have several 𝐏𝐡𝐃 & 𝐏𝐨𝐬𝐭𝐃𝐨𝐜 𝐨𝐩𝐞𝐧𝐢𝐧𝐠𝐬 in our Visual Computing & AI Lab in Munich! Topics have a strong focus on GenAI, including 3DGs
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will work on key research projects applying computer science methods within the context described above. The Professorship of Energy Management Technologies closely collaborates with other professorships
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propose to combine machine learning techniques with formal methods. We will focus on safe reinforcement learning of motion planning problems for autonomous vessels. Motion planning is particularly
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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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processes, and the application of AI methods in engineering. Description: Nowadays, computer-aided manufacturing (CAM) methods are used to a large extent for the production of complex machine components, in
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-Euclidean spaces Scalable layout methods and visual analytics for large and dynamic networks Dimensionality reduction and embeddings for visual exploration Interaction design and user-centered evaluation
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between the fields of computer sciences and architecture. The focus lies mainly on Building Information Modelling, decision-support methods in urban planning and knowledge-based design methods. As part of
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methods to tackle challenges in scientific modeling. Affiliations: Technical University of Munich (TUM) & Helmholtz Munich Niki Kilbertus invites applications for a fully funded PhD position. We’re looking
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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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(WNVI) framework and aims to advance its capabilities in the following directions: • Scalability: Extending methods to high-dimensional and three-dimensional elastography problems using neural operator