31 parallel-and-distributed-computing "UNIS" PhD positions at Nature Careers in Germany
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. The research program may also involve a numerical simulation component. Your tasks #analyzing measurements of ocean turbulence using autonomous glider vehicles #use and develop machine learning methods
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the Reinhart-Koselleck programme for innovative high risk-high gain research. Requirements: university degree in chemistry or physics and profound knowledge in computational and theoretical physics/chemistry
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materialists, electrical engineers, and computer scientists of TUD, RWTH Aachen and Gesellschaft für Angewandte Mikro- und Optoelektronik mbH (AMO ) in Aachen, Forschungszentrum Jülich (FZJ ), Max Planck
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Bioinformatics, Computational Biology, Computer Science, Biomedical Engineering, Computer Engineering, Genetics/Genomics or related field experience with ‘omics platform output experience with biological datasets
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); German language skills are a plus For further information, please contact: Priv.-Doz. Dr. Max Masthoff, max.masthoff@ukmuenster.de , or Univ.-Prof. Dr. Cornelius Faber, faberc@uni-muenster.de More about our group
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or infrastructure. This is what makes our daily work so meaningful and exciting. The Division of Computational Genomics and Systems Genetics is seeking from October 2025 a PhD Student in Deep Learning for Rare
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computational tools for predicting satellite features in XPS spectra of 2D framework materials. Your work will be based on the GW approximation within Green’s function theory. While the GW method reliably
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integrating machine learning and domain-specific knowledge to predict failure arising from hydrogen embrittlement. You will carry out materials testing, computational model development, data processing, and
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qualification program incorporating hybrid lectures, weekly seminars (hybrid and on-site), lab rotations and hands-on training annual summer/winter schools and complementary skills workshops TUD strives to employ
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qualification program incorporating hybrid lectures, weekly seminars (hybrid and on-site), lab rotations and hands-on training annual summer/winter schools and complementary skills workshops TUD strives to employ