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for research. The candidate should possess a good understanding of structural dynamics and coding (MATLAB/Python) with a deep mathematical background. A candidate who demonstrates exceptional aptitude in
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/Qualifications Technical Background: degree in engineering, aeronautics or applied mathematics. Required knowledge: Optimization and Machine learning, Computational Fluid Dynamics, wind turbines (e.g., Openfast
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focus on energy system analysis What you bring to the table ongoing studies in computer science, mathematics, physics, engineering or similar good knowledge of Python previous knowledge in the field
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technologies of pitch bearings for future offshore wind turbines. Funding Notes 1st or 2:1 degree in Engineering, Materials Science, Physics, Chemistry, Applied Mathematics, or other Relevant Discipline. This
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which have a significant impact on the efficiency of power generation, the level of noise produced and the durability of the wind turbine. Advanced computational fluid dynamics and mathematical modeling
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, Materials Science, Physics, Chemistry, Applied Mathematics, or other Relevant Discipline. This project is available only for Self funded students. View DetailsEmail EnquiryApply Online
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damage and its failure mechanism. Funding Notes 1st or 2:1 degree in Engineering, Materials Science, Physics, Chemistry, Applied Mathematics, or other Relevant Discipline. This project is available only
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) Optimization. Funding Notes 1st or 2:1 degree in Engineering, Materials Science, Physics, Chemistry, Applied Mathematics, or other Relevant Discipline. This project is available only for Self funded students
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, the performance of the wind turbine. Funding Notes 1st or 2:1 degree in Engineering, Materials Science, Physics, Chemistry, Applied Mathematics, or other Relevant Discipline. This project is available only for Self