32 cyber-security-data-analysis PhD positions at Chalmers University of Technology in Sweden
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aluminium through AI-driven microstructural analysis. About us The PhD candidate will work at the Division of Data Science and AI , in the neuro-symbolic research group. This group works with combinations
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aluminium in high-value products produced by mega-casting. The main objective of the PhD project is to develop a finite element analysis (FEA) framework that can accurately predict the mechanical properties
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qualifications Marine biogeochemical processes Hydrodynamic processes related to ships, turbulence, or mixing Oceanographic modelling Data analysis and programming (e.g., MATLAB, Python, or R) Interdisciplinary
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emphasis on Image Analysis and/or Geomechanics Fluency in spoken and written English Willingness to learn Swedish, as necessary for providing teaching support at undergraduate level Genuine interest in
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work. A model is to be developed to estimate the material mass breakdown for various cell designs and cell formats. The model will be validated from teardown analysis of commercial lithium-ion battery
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with real-world applications, in collaboration with Volvo Cars and Volvo Group. This is an ideal position for candidates interested in interpretable AI, safety guarantees, and high-impact research in
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mechanical analysis, nanonindentation and atomic force mircroscopy will be used to characterize the mechanical properties of (doped) conjugated polymers. You will work closely with fellow PhD students and
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TRS test section for Chalmers test rig and implement it in the rig with supervision from research engineers at Chalmers. Perform aerothermal measurements in the test rig at Chalmers and use data
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This is a call for a PhD position in the Data Science and AI division at the Department of Computer Science and Engineering (CSE) , Chalmers University of Technology. The department
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gathering knowledge about the diverse physical and geometric properties of objects and dynamic changes in the environment. This involves leveraging rich sensory data—such as vision and touch—encoding