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University of Stavanger invites applicants for a PhD Fellowship in Super-Control of Floating Wind Turbine Farms at the Faculty of Science and Technology, Department of Mechanical and Structural Engineering and
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, the mechanical behaviour of the rock and fractures under stress, and the chemical interactions within the system. The main objective of this project is to advance the understanding of CO2 transport mechanisms in
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in relevant fields of science or engineering, for example: energy engineering, mechanical/chemical engineering, electrical engineering, computer science or discipline closely related to the main duties
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29th August 2024 Languages English Norsk Bokmål English English PhD Fellowship in Geophysical Techniques for CO2 and Energy Storage Apply for this job See advertisement Job description The University of Stavanger invites applicants for a PhD Fellowship in Geophysical Techniques for CO2 and...
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: enthusiastic commitment to interdisciplinary AI research, focusing on security, privacy, and robustness strong foundational knowledge in AI, particularly Large Language Models (LLMs), providing a solid base for
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: enthusiastic commitment to interdisciplinary AI research, focusing on security, privacy, and robustness strong foundational knowledge in AI, particularly Large Language Models (LLMs), providing a solid base for
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and Technology, Department of Mechanical and Structural Engineering and Materials Science. The position is vacant from 01.08.2024 and the starting date is no later than 01.11.2024. This is a trainee
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invites applicants for a PhD Fellowship in Wind Engineering at the Faculty of Science and Technology, Department of Mechanical and Structural Engineering and Materials Science. The position is vacant from
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around the topic. good understanding of chemistry solid skills and knowledge of density functional modeling with common ab initio codes such as Quantum Espresso or VASP. knowledge of semi-empirical codes
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around the topic. good understanding of chemistry solid skills and knowledge of density functional modeling with common ab initio codes such as Quantum Espresso or VASP. knowledge of semi-empirical codes