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The University of Adelaide Research Scholarship is established by the University of Adelaide to support full-time PhD students who are commencing research in pure mathematics in the area of 4
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Mathematical and numerical models of piezoelectric wave energy converters (MPhil or PhD scholarship)
undergraduate degree or equivalent, in applied mathematics, engineering, or a related discipline have experience writing numerical software in a relevant language (e.g., MATLAB, Julia, Python or C) and modelling
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. The specific research areas we will explore are + Adaptive scientific deep learning methods for mathematical physics problems governed by partial differential equations (domain decomposition, adaptive quadrature
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. Candidates with a bachelor's and master's degree in Operations Research, Applied Mathematics, Data Science, Computer Science Engineering, Artificial Intelligence, and Information Technology will also be
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to Operations and Supply Chain Management. Candidates with a bachelor's and master's degree in Operations Research, Applied Mathematics, Data Science, Computer Science Engineering, Artificial Intelligence, and
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, environmental sustainability is defined in the broadest possible sense and is open to applicants from any discipline (including but not exclusive to: engineering, law, mathematics, all the sciences, the social
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This scholarship is open to all local candidates, Australian and New Zealand citizens or permanent residents of Australia. This scholarship is open to all local candidates, Australian and New Zealand citizens or permanent residents of Australia. $34,841 in 2024. The standard duration of a...
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Overview Join us to make a difference! A highly competitive scholarship to develop new statistical machine learning and data-driven methods to battle social disadvantage in NSW. You will work with
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learning and/or natural language processing. Strong academic performance in computer science at undergraduate and masters level, with evidence of prior research experience in machine learning and/or natural
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-preserving trustworthy distributed machine learning. In this research, the successful candidates will focus on mathematical backgrounds involved in differential privacy to devise novel scalable approaches