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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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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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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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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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Experience with performing laboratory experiments Ability to work with large data sets (> 500 GB) Numerical modelling Main responsibilities Independent research and research training (80% of time) Support for
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failures. We offer access to unique experimental data and computational tools developed by our research team for addressing a timely societally relevant problem. Project overview The aim is to unravel
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of the numerical methods behind CFD and turbulence models. Experience in analyzing CFD data and interpreting simulation results. Excellent command of written and spoken English. Experience writing scientific reports
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long-term, and most often global, perspectives on future renewable fuels for transport. We seek to rigorously analyse the feasibility of energy transitions, utilize empirical as well as estimated data