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existing quantitative methods in international nuclear safeguards with state-of-the-art artificial intelligence/machine learning (AI/ML) algorithms Contribute to standardising methodologies for calculating
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Do a PostDoc in Pathology AI! 11.10.2023, Wissenschaftliches Personal The Computational Pathology Lab at the Technical University of Munich (TUM), TUM School of Computation, Information and
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, and characterization Develop gate implementations, benchmarking and algorithms Work on the interdisciplinary challenges in systems engineering Install and improve experimental setups and fabrication
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methods, machine learning algorithms, and prototypical systems controlling complex energy systems like buildings, electricity distribution grids and thermal systems for a sustainable future. These systems
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retinal tissue biopsy. The project is funded by the Emmy Noether programme of the German Research Foundation (DFG) for a three-year period, with the possibility of an additional three years. We offer: a
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2040 programme. After reaching scientific gain in laser-driven ICF experiments at the National Ignition Facility, there is a global endeavour to turn the scientific milestone into practical application
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14.12.2022, Wissenschaftliches Personal The BMBF-funded position is part of the CoMPS project, which is a multidisciplinary project combining the fields of mathematics, computer science, geophysics
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further opportunities for interdisciplinary training. For more information about the research and study program, visit: https://www.lai.fuberlin.de/en/temporalities-offuture/index.html Job description
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Max Planck Institute for Plasma Physics (Greifswald), Greifswald | Greifswald, Mecklenburg Vorpommern | Germany | about 1 month ago
of the leading centres for fusion research and is engaged in developing the physical foundations for a future fusion power plant. The institute is affiliated to the European Fusion Programme. The Max-Planck
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coding experience with e.g. Python/Matlab/R Practical experience with High Performance Computing, and scientific programming and a willingness to learn to work with high-performing computing systems