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in recruitment. If you find the position interesting but do not think you meet all our requirements, apply anyway—you could be the ideal candidate for us. You must have a two-year master's degree (120
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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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reporting in English Creative, proactive and independent thinking Prior experience in research in the form of student projects, and capability to work in an interdisciplinary manner are a plus. The successful
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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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. 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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-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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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