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prediction of regional climate and extremes using hybrid physics-AI models. About the project/work tasks There is a growing need for subseasonal-to-seasonal (S2S; 2 weeks to 12 months) predictions of regional
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team. The position will include onsite training in clinical medical physics and exciting research in imaging and radiation therapy. This is a great opportunity to join the medical physics community with
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expertise in MRI physics, obstetrics, placental biology, biomedical engineering, mathematics, computer science and artificial intelligence. The team includes researchers from the University of Nottingham
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- and the people who discover them The Opportunity Join the Faculty of Science at Monash University’s School of Physics and Astronomy and contribute to cutting-edge research in experimental condensed
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, project lead, at [email protected] Next steps in the recruitment process It is anticipated that the selection process will take place in the week commencing 5th October. This will consist
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goals will also be explored during the later stages of the selection process. You should also have: solid knowledge of artificial intelligence and machine learning techniques, including their limitations
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external partners in physics, materials science, and engineering Publish research outcomes in high-impact journals and present findings at international conferences
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to advance nearshore hydrodynamic modelling by integrating data-driven and physics-based approaches for simulating wave propagation, wave transformation, and wave–current interaction from deep water to shallow
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prototyping of intelligent HVOF spraying equipment with integrated control systems; (c) contribute to the development of multi sensor fusion technologies for defect prediction and process parameter
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lengths, with emphasis on contact engineering, access resistance reduction, and threshold voltage control. • Execute full process flows in the NUS cleanroom, including lithography, etch, deposition, and