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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Hey machine learning enthusiast with a love for physics and
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safety and nuclear energy technologies. Job requirements You hold, or will soon obtain, a Master's degree in applied physics, mechanical engineering or a related field. You have a strong interest in
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Are you fascinated by the intersection of Physics, Chemistry and materials science? Do you want to contribute to protecting monuments including World Heritage Sites from degradation caused by rising
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scientific knowledge, such as physical laws, differential equations, and domain-specific constraints, to model, simulate, and understand complex systems. The project will explore modern SciML methods
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Are you fascinated by controlling magnetic matter by femtosecond laser pulses, eager to explore the underlying physical mechanisms, and passionate to develop a generic tool to ‘print’ complex
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combines microfluidics, bubble physics, and ultrasound signal processing to bring nanobubble imaging closer to clinical use. You will collaborate closely with a fellow PhD candidate, a postdoc, and a
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measurements and process-based modelling to identify the mechanisms linking vegetation, soil microorganisms and ecosystem carbon cycling. The project spans laboratory, field and ecosystem scales and combines
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physics and building high performance imaging systems. She or he has a demonstrable interest in optics, signal processing, and mathematics or machine learning. The candidate should have an MSc degree in
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well as a wise use of machine learning methods. The candidate should hold an MSc degree in Applied Physics, Electrical Engineering, or the equivalent. The PhD position is firmly embedded in a physics
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implications for both fundamental and medical sciences. Job requirements MSc degree (or nearing completion) in physics, biophysics, computational biology, or a related field. Strong programming skills (Python