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pa Fixed term Ref: 095093 You will join the group of Professor Alessandro Troisi based in the Materials Innovation Factory (https://www.liverpool.ac.uk/materials-innovation-factory/ ) to work on a
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university research into commercial outcomes. Under this program, PhD students will gain unique skills to focus on impact-driven research. This Project aims to develop a predictive machine learning model
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applicant will receive a tax-free stipend, at the current value of $36,063 per annum 2025 full-time rate, as per the Monash Research Training Program (RTP) Stipend www.monash.edu/study/fees-scholarships
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. This project will explore recent advancements in implicit neural representations, which have demonstrated effective neural network activations for computer vision. Our goal is to design new PINN architectures
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-effective safety roller barriers using recycled tyres and design optimisation About the Role The continued surge of Electric vehicle (EV) ownership in Australia is steadily increasing, however their unique
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PhD Scholarship in Digital Mapping of Homemade & DIY Cultural Economies in First Nations Communities
appointment Remuneration: The successful applicant will receive a Research Living Allowance, at current value of $52,352 AUD per annum 2025 full-time rate (tax-free stipend), indexed plus allowances as per RTP
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: Full-time Duration: 3-year fixed-term appointment Remuneration: The successful applicant will receive a tax-free stipend, at the current value of $36,063 per annum 2025 full-time rate, as per the Monash
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Applied mathematics, fluid mechanics, high-performance computer simulations. Full time, fixed term position (3 years) at Hawthorn campus $34,700 per annum (2025 rate) About the Scholarship Higher
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Statistics for the Australian Grains Industry 3 (SAGI3). Investment. The University of Adelaide, in collaboration with Curtin University and The University of Queensland, is leveraging machine learning, data
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/ defensive) or different game context scenarios (inside-25 m entries / defensive-25 m exits / stoppage / etc) to the game. Current training session drill design lacks individualisation and has the potential