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subject or subject relevant to the proposed PhD project (inc. computing, mathematics, engineering etc.). Enthusiasm for research, the ability to think and work independently, excellent analytical skills and
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Phd Studentship in Computer Science: Empirical Security Assessment of AI Decision Engines in Cyber-Physical Systems Award Summary 100% home fees covered, and a minimum tax-free annual living
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, including cutting edge quantum physics and chemistry, material science, nanotechnology, biochemistry, cell biology, or medical research. The SNI PhD programme includes multiple social events, trainings in
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focus on computational material science (both at the macroscale and atomic scale), biomedical engineering/ biomechanics, and process engineering. However, also applications in environmental modeling (in
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Max Planck Institute for the Structure and Dynamics of Matter, Hamburg | Hamburg, Hamburg | Germany | about 9 hours ago
-fast phenomena, X-ray physics and dynamical imaging in all areas of science, covering physics, chemistry and biology. 23 interdisciplinary PhD positions in Ultrafast Science and Quantum Materials – IMPRS
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FieldEngineering » Communication engineeringEducation LevelMaster Degree or equivalent Skills/Qualifications M.Sc. degree in Electrical engineering, Telecommunications, Computer science, Robotics, or similar domain
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diverse research network spanning AI, computer science, mathematics, engineering, physics, and the life sciences. What we offer A structured three-year PhD program at the interface of AI and biomedical
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29 Aug 2026 Job Information Organisation/Company ARCNL Research Field Engineering » Computer engineering Engineering » Precision engineering Physics » Computational physics Physics » Metrology
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The Department of Chemistry, Section for Chemical Biology invites applicants for a PhD fellowship in chemical methods for half-life extension of therapeutic peptides. The project is part of
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physics-informed neural networks (PINNs). However, these approaches are still in their early stages of development and have yet to demonstrate their effectiveness for complex real engineering problems