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Field
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project team regularly use for the production of model colloidal films, ceramic dielectrics, photovoltaics and battery electrodes to provide the datasets required to educate the machine learning algorithms
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have designed and introduced new control laws into Trent gas turbine engines and developed algorithms monitoring fleets of 100s of engines flying all around the world. During the PhD, you will have the
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(UNSW), Prof. Brendan McKay (ANU) and Prof. Ian Wanless (Monash). The project aims to develop new theoretical tools to address fundamental challenges about graphs and hypergraphs with given degrees
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is encouraged to apply. A successful candidate would develop a research and teaching agenda around: Co-Designing algorithms and hardware for processing massive amounts of high-dimensional streaming
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intelligence, A/Prof Gruber’s team focuses on the development and validation of biological ageing clocks for clinical translation and application. Appointments will be made on a two-year contract basis, in
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. The task of the theory group led by Prof Kyriienko at the University of Sheffield within the consortium is to lead nationally the development of quantum machine learning (QML) algorithms. The research will
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. Applicants should have strong expertise in computational analysis of electrophysiological data as well as proficiency in large language models and machine learning algorithms. First-hand experience in
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to test the current algorithm and inform development of future algorithm refinements aimed at supporting diabetic foot ulcer (DFU) prevention through identification of temperature differences of > 2.2°C
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developing a machine learning (ML) algorithm for the automated analysis of the above-mentioned mass spectra. Desirable: - knowledge in the field of Planetary Sciences - very good written and spoken English (C1
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faculty in developing theory and application tools for artificial intelligence (AI), and training efficient data analytics. 60% - Leading research in AI will include generative models, algorithms and