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We are looking for a highly motivated, skilled, and persistent PhD student with experience in computational fluid dynamics (CFD) and some knowledge in structural analysis. The research aims
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This PhD project focuses on strengthening network security for large-scale distributed AI training. As training increasingly spans multiple data centers connected over wide-area networks, it
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This PhD project focuses on advancing network security in the emerging Web3 ecosystem. As decentralized applications built on blockchain and distributed ledger technologies become more widespread
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your application: Proven experience with data analysis and programming (e.g., GAMS, Matlab, Python or R). 7.5 credit course (or more) in sustainable energy futures Experience of other energy and
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qualifications Documented experience with data analysis and programming (e.g., Matlab, Python or R). Experience of risk assessment and/or decision analysis Experience of probabilistic methods such as Monte Carlo
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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