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posts Starting date: 24.05.2024 Job description:2 Postdocs in Deep Learning for Earth System Science - Reference code: 50117505_2 ? 2024/KS 2 Commencement date: as soon as possible Work location
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for science, with scalable modern methods, interdisciplinary expertise and industrial-scale computation. A solid background in deep learning is required, including some published work. Expertise in Earth system
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | about 2 months ago
of foundational models in the context of observation (mainly based on transformer architectures) Your profile # Completed university studies (Master/PhD) in natural sciences, mathematics, earth and environment
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EUMETSAT - European Organisation for the Exploitation of Meteorological Satellites | Darmstadt, Hessen | Germany | about 1 month ago
Environmental science » Earth science Physics Technology » Space technology Researcher Profile First Stage Researcher (R1) Established Researcher (R3) Country Germany Application Deadline 19 Jun 2024 - 21:59 (UTC
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Job Offer from June 01, 2024 The Max Planck Institute for Gravitational Physics (Albert Einstein Institute) is the largest research institute in the world specializing in general relativity and
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Professorship (W3) for Informatics with a focus on Software Technology Institution: Faculty of Mathematics, Informatics and Natural Sciences Commencement of duties: Summer Semester 2025 Application
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3 Jun 2024 Job Information Organisation/Company Universität Leipzig Department Faculty of Mathematics and Computer Science Research Field Computer science Researcher Profile Established Researcher
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technology of active fluoride fibers. The position forms part of the Laser Technology (LAS) department, which develops and evaluates specific photonic materials and components, associated laser sources and
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training on the High Performance Computers, including JUPITER, Europe`s first exascale computer Prepare, process and publish datasets and benchmarks for self-supervised learning in science Engage in national
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-supervised learning in science Engage in national and international ML/DL communities, most importantly the Helmholtz Foundation Model Initiative Present research results at scientific meetings, conferences