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-aware learning methods with domain decomposition techniques, enabling parallel training and efficient GPU-supported implementation. Your tasks: Development of physics-aware ML models for 3D blood-flow
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strong background in applied mathematics Excellent programming skills (Python, C/C++) Good experience in machine learning and parallel computing Good organisational skills and ability to work both
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related in space and time and to behavioral events. Core Tasks: Getting familiar with the experimental data and the concepts of neuronal coding, and Elephant Analysis of the parallel rate data for
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. Your Profile: A Masters degreee with a strong academic background in physics, mathematics, computer science, or a related field Proficiency in at least one programming language (Python, C
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Karlsruher Institut für Technologie (KIT) | Karlsruhe, Baden W rttemberg | Germany | about 2 months ago
Germany Application Deadline 28 Nov 2025 - 22:59 (UTC) Type of Contract To be defined Job Status Other Offer Starting Date 30 Oct 2025 Is the job funded through the EU Research Framework Programme? Not
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program generation and optimization Verification, testing and security of software systems Explainability of AI and of software engineering Software for distributed, highly-parallel AI systems Intelligent
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engineering Very strong mathematical and algorithmic background Programming experience (Python, C++, etc.) Familiarity with parallel programming frameworks (e.g. MPI, CUDA) Fluent in written and spoken English
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GPU-capable, parallelized simulation frameworks. Work closely with experts in HPC and power systems to enhance scalability and computational performance. Disseminate your findings through scientific
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, Statistical Physics, Genome Annotation, and/or related fields Practical experience with High Performance Computing Systems as well as parallel/distributed programming Very good command of written and spoken
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) The Institute of Computer Engineering (ZITI) at Heidelberg University invites applications for one research assistant position with the possibility to do a PhD in parallel at the chair of computer architecture