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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
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systematic phases: first, establishing a robust data foundation; second, designing a modular and open digital platform; and third, developing a predictive maintenance application as a proof of concept
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-small silicon nanocavities [Babar2023, Rosiek2023] with extreme light-matter interactions. We aim to combine fundamental theory, device design, and our unrivalled capabilities in high-resolution silicon
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: Theoretical understanding of photonic integrated circuits. Additionally, we expect that you: are academically curious and think deeply and creatively. have a strong internal drive and take responsibility
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. Your work will focus on developing physics-informed AI methods to enhance decision-making in design and operation of next generation thermal energy storage systems, such as latent heat TES and
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an "all-in-one" solution by integrating advanced passive components with semiconductor power devices, driving a fundamental transformation in power electronics design and manufacturing through heterogeneous
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(a) networked multi-agent human-robotic systems that work collaboratively in a well-coordinated and safe manner, (b) computational design and digital manufacturing of components, (c) design of
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welcome candidates with varied experiences and educational pathways. DTU Wind works with an inclusive mindset in recruitment. If you find the position interesting but do not think you meet all our