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for practical medical use. This project aims to create accurate and rapid surrogate models by combining physics-aware learning methods with domain decomposition techniques, enabling parallel training and
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19 Jan 2026 Job Information Organisation/Company Forschungszentrum Jülich Research Field All Researcher Profile First Stage Researcher (R1) Application Deadline 19 Jan 2038 - 03:14 (UTC) Country Germany Type of Contract To be defined Job Status Other Is the job funded through the EU Research...
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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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Your Job: This PhD project bridges between classical analytical methods and modern AI based techniques to analyse spike train recordings to advance our understanding of neural population coding while maintaining clarity in the interpretation of results. Concurrently, AI-based methods are...
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classical calibration pipelines, including camera models, calibration targets, and algorithms, followed by an overview of our in-house specialized methods. In parallel, you will work in experimental setups
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Future. Discover. Together. The introduction of AI applications places high demands on optical connections in data centers. In addition to the approach of fewer parallel channels with very high data
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- experience with HPC clusters, parallel or distributed computing - German language skills We offer - a cutting-edge research environment at PETRA III imaging beamlines - collaboration with leading institutions
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organizational skills experience with HPC clusters, parallel or distributed computing German language skills We offer a cutting-edge research environment at PETRA III imaging beamlines collaboration with leading
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measurements, and simulation results Integrate data engineering workflows with HPC-based simulation environments Optimize and parallelize software solutions for execution on one of the world’s most powerful and
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standards for the use (and development of policy around) AI in disaster management. In parallel, Fraunhofer HHI is contributing to the Working Group on Digital Transformation for Hydrology and Water Resources