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scientific development of design tools and assessment frameworks that enable circularity in durable aerospace components. You will generate insights that directly inform the design process in other work
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they learn, PRL134, 147402 (2025). Qualifications We seek candidates with: A PhD in physics, applied mathematics, materials science, mechanical engineering, computer science, or a related field. Strong
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of the queer intellectual in close collaboration with the research team (including the PI and the PhD); publishing in leading international peer-reviewed journals and contributing to a final edited
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; the advent of the Solar System internet and the associated challenges in network management and operations concepts, for example, new forms of user-machine interfaces, such as AR/VR; new ways to leverage
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, collaborate openly across institutions, and have the stamina to push through the engineering challenges that come with real-world physical AI. Your experience and profile: a PhD degree in Computer Vision
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multimodal modeling, interaction design, and adaptive systems. Job requirements We are looking for applicants who have or expect to receive a PhD degree before joining the project. Applications have a relevant
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transition, we encourage you to apply. Job requirements PhD degree in Chemistry, Materials Science, Physics, or a closely related field (completed by the time of appointment). Demonstrated expertise in
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in data integration, model design, and large-scale training by combining multi-modal scientific data, knowledge graphs, physics-aware machine learning, and GPU/HPC computing to develop transparent and
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collaboration with a PhD student at the faculty of Industrial Design Engineering of TU Delft. You will be working on the sensing system in the armband. This will include the sensing yarn, a microfluidics system
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or writing sample you are particularly proud of; Contact information for two academic references, preferably including your PhD supervisor, who may be contacted during the selection process; The first round of