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Field
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dedicated researcher with a PhD in mathematics, electrical or mechanical engineering, computer science or a related field, and a strong methodological background in machine learning. The ideal candidate has
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combining artificial intelligence with human expertise. The lab develops knowledge-grounded artificial intelligence, text mining and knowledge assembly, mathematical and systems modeling, and causal analysis
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. About You You will have a PhD in computer science, engineering, mathematics, or similar, strong programming skills, and experience with a contemporary machine-learning framework such as PyTorch. You will
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. About You You will have a PhD in computational engineering, applied mathematics, bioengineering, mechanical engineering or a related discipline, with strong experience in CFD or numerical simulation. You
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excellent opportunities to publish in high-impact journals, collaborate with leading European partners, supervise MSc and PhD students, and contribute to the development of innovative battery and charging
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, scientific computing, mathematics, statistics or a related field, or a foreign degree equivalent to a PhD degree in machine learning, computer science, scientific computing, mathematics, statistics or a
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experience). • Education: PhD or equivalent degree in mechanical engineering, physics, or applied mathematics or related disciplines. • Laboratory experience: mechanical and dynamical measurements, 3-D
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European partners, supervise MSc and PhD students, and contribute to the development of innovative battery and charging solutions to accelerate the energy transition to climate-neutral cities. The research
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interdisciplinary research culture. Person Specification Applicants should have a PhD awarded, or a PhD thesis submitted, in Theoretical Physics, Mathematics or a closely related discipline. They should have
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collegial and interdisciplinary research culture. Person Specification Applicants should have a PhD awarded, or a PhD thesis submitted, in Theoretical Physics, Mathematics or a closely related discipline