464 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Univ" positions in Germany
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mobile security. You already have knowledge of software development for Apple iOS devices or are interested in learning about it. You are also well versed in reverse engineering. You are fluent in written
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(FIJI/ImageJ etc.) Ability to work independently and to supervise interns and undergraduates Excellent English (in speaking and writing) and computer skills, knowledge of German is a bonus, but not
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• numerical simulations and computer programming (e.g., Python and LabVIEW) • Developing back-of-the-envelope estimates for complex physical problems. Applications should be sent by e-mail, together
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to you as soon as possible and let you know what happens next. Fraunhofer Institute for Computer Graphics Research IGD www.igd.fraunhofer.de Requisition Number: 82481 Application Deadline
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to expect: Structured, hands-on training: During your first two years, you’ll complete lab rotations in at least two DIGS-ILS research groups — building skills, learning new techniques, and connecting with
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learn microinterventions, such as taking blood samples from specific vessels of mice. Experience and FELASA-B certificates are an advantage. MS Office skills; experience with image processing software is
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development opportunities (e.g., heiTRACKS) Competitive salary and extensive benefits Possibility to teach in the area of your expertise (English or German) The remuneration is based on pay grade TV-L 13. We
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Max Planck Institute of Immunobiology and Epigenetics • | Freiburg im Breisgau, Baden W rttemberg | Germany | 1 day ago
epigenetics, biophysics, metabolism, biochemistry, cell biology, proteomics, bioinformatics and functional genomics. We train doctoral researchers to become self-reliant and to acquire and utilise the knowledge
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research institution and have the opportunity to apply the theoretical knowledge you have acquired during your studies in a practical setting. You will learn about our structures and processes in
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general approaches from cognitive science (resource-rational analysis) to investigate in how far LLMs may acquire “causal world models”. The focus of the project is on the latent representations in LLMs