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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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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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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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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
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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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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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of the closing date. Any queries regarding the application process may be addressed to [email protected] . Please quote reference ITD-DIB-2026-11. The supporting statement section should set out how your
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through field-based surveys, and from ground-based sensors, proximal sensors and UAVs and satellites. These data are often used to drive process models, that ultimately are used to optimise aspects
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of bioelectrochemical systems, electrochemical engineering, resource recovery and sustainable battery recycling. The project aims to translate a laboratory-validated lithium recovery process into a continuous-flow
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at UniMelb. We're committed to a barrier-free recruitment process and ongoing workplace support, providing adjustments throughout. We warmly encourage applications from people with disabilities. Learn more