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simulation experience; collaboration with leading researchers; and training in advanced characterisation, data analysis, and data interpretation. Number Of Awards 1 Start Date 1st October 2026 Award Duration 4
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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) Payment technologies and the future of money Explainable artificial intelligence (AI) in financial services Integration of FinTech and big data in financial markets and sustainable finance. To discuss the
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Doctor of Philosophy (PhD) graduate researchers, in which the primary data for the PhD thesis can be collected only in a field location (for example, a fundable project may require access to particular
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● Electrical and Computer Systems Engineering ● Materials Science and Engineering ● Mechanical and Aerospace Engineering For further information, please follow the link for each Graduate Research Degree ● 3291
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environmental uses of freshwater is probably Australia’s most critical challenge. We are looking for candidates with strong economics training as a background, though other relevant disciplines (such as data
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forms and further information on the application procedure can be found here . Application Deadline Applications may be submitted at any time; there are, however, specific timelines which are detailed
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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candidate is expected to hold: A master degree in biomedical engineering or computer science, Excellent programming skills (Python). Experience with data curation, large-scale datasets, and machine learning
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properties through computer simulations. The project also includes validation of materials in the lab and translating the findings into practical recommendations for use in real power-electronics environments