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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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ultrasonic sensors for real-time seal gap measurement. Combine experimental research and mathematical modelling to pioneer innovative sealing solutions. What We Offer Full 4-year Funding for UK applicants
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solving. Diverse research areas: Work on numerical models, analyzing large data sets, statistical methods and more in a unique scientific environment. Who Should Apply? Emphasizing the physical system
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benchmarking. References: Flemisch, Darcis, Erbertseder, Faigle, Lauser, Mosthaf, Müthing, Nuske, Tatomir, Wolff, Helmig 2011. DuMux: DUNE for multi-phase,component,scale,physics,… flow and transport in porous
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
publications and project reports Your Profile: Strong motivation for an interdisciplinary project that combines numerical models, experiments, and artificial intelligence A master`s degree or diploma in physics
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Communications Dr Jessica Jay, School of Mathematical Sciences Dr Dan Fretwell, School of Mathematical Sciences Qualifications and Experience We are looking for motivated individuals who are eager to tackle real
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Institute for Marine and Atmospheric Research is looking for a motivated PhD candidate with a background in physics, applied mathematics, meteorology, geosciences or a related field. You will work within the
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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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define observable events based on expert knowledge and available evidence. Development of a post-race analysis structure, process and data ‘toolkit’ that can build on historical understanding of race
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focus on the newly-discovered physical and chemical properties that arise from the behaviour of matter at the nanoscale. ICN2 has been awarded with the Severo Ochoa Center of Excellence distinction