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sustainable future through materials science. All early-stage researchers recruited into the WISE programme will be a part of the WISE Research School , an ambitious nationwide programme of seminars, courses
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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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information about us, please visit: the Department of Biochemistry and Biophysics . About the DDLS PhD student program Data-driven life science (DDLS) uses data, computational methods and artificial
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implementation. About the project Reactive synthesis refers to the automatic generation of programs from high-level behavioral specifications. This approach plays an increasingly important role in areas such as
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another way. You should have excellent programming skills, preferably C++, and good knowledge of graphics programming. Furthermore you should also enjoy solving algorithmic challenges. The position also
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competitive performance. This position is supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP). WASP is Sweden’s largest individual research program ever, a major national initiative
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that enable energy-intensive industries to plan and optimize their production based on energy demand, power consumption, and sustainability. The current PhD position focuses on analyzing how digitalization and
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artificial intelligence is transforming human culture and collective memory. The Wallenberg AI, Autonomous Systems and Software Program – Humanity and Society (WASP-HS) is a national research program in
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legitimacy. WASP-HS The PhD position is part of the Wallenberg AI, Autonomous Systems and Software Program – Humanity and Society (WASP-HS). The vision of WASP-HS is to foster novel interdisciplinary knowledge