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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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) Expertise in further programming languages (in particular C++), GPU programming, parallel programming or high-performance computing are highly valued Keen interest in neuroscience is essential Experience with
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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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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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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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- 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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with a focus on efficiency and the prioritization of parallel projects. What we offer Fascinating challenges in a scientific and entrepreneurial setting Attractive salary package according to TvöD with
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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