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Identify new applications for Machine Learning in science, engineering, and technology Develop, implement and refine ML techniques Implement parallel ML training on the High Performance Computers Engage in
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, parallel/distributed computing, as well as diverse architectures and understanding of its impact on application performance Knowledge in GPU-based programming and modelling of scientific simulations
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and spatial distribution” in the Research Unit Coastal Seas and Society until the 30.11.2027 and a percentage of 100% (40h/week), subject to the funding of the project. Remuneration is paid in
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statistical/mathematical methods to analyse large data sets Comprehensive experience with HPC system usage, parallel/distributed computing, as well as diverse architectures and understanding of its impact on
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: Master degree in Technomathematics or in computer science, engineering, physics, mathematics or natural science or equivalent degree Comprehensive experience with HPC system usage, parallel/distributed
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to analyse large data sets Comprehensive experience with HPC system usage, parallel/distributed computing, as well as diverse architectures and understanding of its impact on application performance Firm
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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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Hint Due to serious budgetary cuts there will be no further calls for the German Chancellor Fellowship Programme. • The fellowships granted to the current cohort of Federal Chancellor Fellows 2023
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, Physics, or similar fields Self-motivated personality with very good command of written/spoken English Comprehensive experience using HPC systems as well as parallel/distributed computing with CPUs and GPUs
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Professorship - Programme Information (PDF, 123 KB) Recently selected Humboldt Professors Our Alexander von Humboldt Professors for AI WANTED: Alexander von Humboldt Professors (female) The Alexander von Humboldt