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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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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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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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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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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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. The position is placed in the Division for Computer Networks and Systems and is formally employed by Chalmers University of Technology. Our research spans from theoretical computer science to applied systems