13 electronics-engineering-"https:"-"https:"-"https:"-"https:"-"https:"-"HFML-FELIX" Fellowship positions in Germany
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Sciences - Department of Physik Research fellow {m/f/d) in the field of novel electronic materials with part-time employment (75 %) limited to 4 years - E 13 TV-L HU Your responsibilities: - scientific
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Max Planck Institute for the History of Science, Berlin | Berlin, Berlin | Germany | about 2 hours ago
. Applicants (m/f/d) should demonstrate their commitment to a research topic related to the history of science, technology, and medicine, or science and technology studies, and a need to work with an
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The Käte Hamburger Centre for Cultural Practices of Reparation (KHK CURE) at Saarland University (UdS) is an institute for advanced study, funded by the German Ministry for Research, Technology and
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available in the further tabs (e.g. “Application requirements”). Programme Description The Indo-German Science & Technology Centre (IGSTC), established as a joint initiative of the Department of Science and
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researcher in Computer Science, Data Science, Human-Computer Interaction, Psychology, Empirical Educational Research, Learning Sciences, Cognitive Science, or related disciplines who is eager to contribute
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research, the programme encourages technology transfer, real-world applications, and engagement with innovation and startup ecosystems. By connecting global talent with leading research, industry, and
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Machine Learning Group, Department of Engineering, CambridgeMLG Cambridge About Us News Research Publications People PhD Admissions Blog Latest News Papers with MLG authors to appear at ICML and
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medicine or for an MSc or PhD (or equivalent) in medical engineering, applied medical sciences, or public health. It funds students from Germany who wish to carry out research stays, internships or part of a
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fields such as computer vision and natural language processing, graph-structured data remain a rich frontier for methodological innovation, with many fundamental challenges and exciting opportunities ahead
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of molecular data. While machine learning has transformed fields such as computer vision and natural language processing, the molecular life sciences remain a rich frontier for methodological innovation