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Qualifications / Discipline: Graduating PhD or recent PhD holder specializing in optimization. Skills: Advanced knowledge on nonsmooth analysis, Riemannian optimization, nonconvex optimization theory and
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of thermoplastic composites. Work closely with other work packages (WP) within the program. Qualifications PhD from reputable university in applied mechanics. Expertise in fiber-reinforced composites. Proficient in
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CST microwave Studio, composite material fabrication, microstructural characterization, and microwave measurements. The candidate should have a PhD degree on relevant areas, e.g., mechanical engineering
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CST microwave Studio, composite material fabrication, microstructural characterization, and microwave measurements. The candidate should have a PhD degree on relevant areas, e.g., mechanical engineering
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CST microwave Studio, composite material fabrication, microstructural characterization, and microwave measurements. The candidate should have a PhD degree on relevant areas, e.g., mechanical engineering
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interaction Design algorithms for dialogue systems Integrate commonsense knowledge representation and reasoning in the system Job Requirements: Possess a PhD in Computer Science or related disciplines Strong
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on biological aspects of alternative protein technology Job Requirements: PhD Degree in molecular biology, and related degrees Experience in cell differentiation, particularly adipose cells biology; cultivated
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on numerical simulation study of local sediment transport (by particle method and finite volume method) and experimental study. Job Requirements • Possess a recognised PhD degree in civil engineering or a
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duties related to the research program. Job Requirements: A PhD in Computer Science, Quantum Computing, or relevant fields. Strong background in quantum computing and quantum machine learning. Strong
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to the research program. Job Requirements: A PhD in Computer Science or relevant fields. Strong background in deep learning and neural rendering. Excellent programming skills to implement and deploy deep learning