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, and innovative research groups that comprise everything from basic science to strategic and applied research. The activities encompass research and education within materials, mechanics, physics
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research ethics, and commitment to research quality. Who we are The Computational Physics and Machine Learning Lab led by prof. Lucantonio is a newly established group within the Mechanics and Materials
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-efficient magnetic heating/cooling device. Qualified applicants must have: PhD degree in physics, astronomy, engineering, computer science or similar. Experience with finite element modeling, ideally Comsol
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2026 - 23:00 (UTC) Type of Contract To be defined Job Status Full-time Hours Per Week To be defined Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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and working with Master and Ph.D. students at ECE and collaborators as needed. Your profile Applicants should hold a PhD in Electrical Engineering, Electronics Engineering, Materials Science, Physics
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demonstrated expertise in experimental quantum optics and a PhD (or equivalent) in physics, quantum information science, or a related field. We expect you to check multiple of these boxes: Expertise in quantum
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graph algorithms for optimization under physical constraints Applying graph mining and graph data management techniques Designing computational methods for waste heat reuse and green transition goals
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this project will feed into a central model (developed in a parallel CEBE work package) linking the parameters of constitutive material model to physical and chemical properties across scales supported by AI
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Job Description If you wish to develop your research within Science & Technology Studies (STS) and Computational Anthropology, you may consider applying for this Post Doc position (36 months). We
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the Division for Geomagnetism and Geospace, an internationally leading research environment with strong expertise in space physics, geomagnetism, and data analysis. This position is connected with the ERC