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strong interest in aluminum alloys, fatigue analysis, and numerical modelling is preferred. Experience with computer aided design and engineering (CAE, e.g., Abaqus, Ansys) software tools commonly used in
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in a variety of lossy media. The project will give you an opportunity to work with theoretical, numerical and experimental aspects of machine learning assisted design of antennas and metasurfaces
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, including 4 training schools and two workshops. As a participant of the project, the PhD student will become part of a team at DTU with numerical and experimental expertise in photonic computing
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doctoral candidate who meets the following requirements: A background and strong interest in aluminum alloys, fatigue analysis, and numerical modelling is preferred. Experience with computer aided design and
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. students in the doctoral network, including 4 training schools and two workshops. As a participant of the project, the PhD student will become part of a team at DTU with numerical and experimental expertise
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schools and two workshops. As a participant of the project, the PhD student will become part of a team at DTU with numerical and experimental expertise in photonic computing. The activities within
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the other 14 Ph.D. students in the doctoral network, including 4 training schools and two workshops. As a participant of the project, the PhD student will become part of a team at DTU with numerical and
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the project, the PhD student will become part of a team at DTU with numerical and experimental expertise in photonic computing. The activities within the project will benefit from synergies with other
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network, including 4 training schools and two workshops. As a participant of the project, the PhD student will become part of a team at DTU with numerical and experimental expertise in photonic computing
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and quantitative sustainability assessment methods, including Life Cycle Assessment (LCA), Energy System Analysis (ESA), and socio-economic modeling. The candidate will be expected to contribute