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the instructions for applicants on the ACSPRI Fellowship Program website. About the scholarship PhD candidates at ACSPRI Member Institutions are invited to apply for the 2024-25 ACSPRI Fellowship Program. Valued
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validation of advanced algorithms for disease detection, contributing to Australia’s data-driven crop health monitoring systems. This work will support sustainable crop production and enhance national
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an opportunity for a Postdoctoral Fellow. You will contribute to UNSW’s research efforts in developing machine learning algorithm for photovoltaic applications and utilising them for the investigation
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Massachusetts Institute of Technology (MIT) in Cambridge, Massachusetts. Your key responsibilities will be to: design and implement mathematical algorithms, and facilitate their integration into Magma engage with
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-based hail climatology for France, Switzerland and Northern Italy, including hail swaths per event across more than a decade. Design, develop and train geostationary satellite-based hail algorithms using
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, Massachusetts. Your key responsibilities will be to: design and implement mathematical algorithms, and facilitate their integration into Magma engage with users, researchers, and developers, both internally
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: Research: Development and validation of predictive maintenance algorithms for solar farms. Interface with industry partners for knowledge sharing and feedback. Play a key role in reporting to the funding
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algorithms and methods for adaptive and personalised feedback, modelling learning behaviours with sequence and deep learning methods, and generating interpretable insights through novel analytics and
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information, hydrologic data and survey records. Skills and Experience To be considered for this position, you will have: completed a PhD or equivalent qualifications or research experience a record of
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of classical and hybrid classical-quantum algorithms for treating the correlations. This position offers exciting opportunities for collaboration within UQ, across the QDA network, and with external research