14 big-data-and-machine-learning-phd Fellowship positions at University of Sydney in Australia
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are looking for a Postdoctoral Research Fellow who has: a PhD (or in near completion) in the relevant fields of Artificial Intelligence, Machine Learning, HCI demonstrated contributions to publications in top
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diverse audiences. Well-developed computer literacy, research skills, planning, organisation, and customer service abilities. About you as an Academic Level C Senior Research Fellow (in
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characterisations using impactors and liquid chromatography Strong planning, organisation, and computer literacy skills, with the ability to manage research projects and competing priorities effectively. Excellent
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immunotherapy PhD in immunology significant experience conducting original research and engaging in scholarly activity expertise in novel CAR-T design and epigenetic analyses of human CAR-T cells and T cell
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a $50 million investment from the Snow family over 10 years. Our mission is to develop life-changing treatments for glaucoma and other optic nerve diseases that cause irreversible blindness. Learn
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-making processes in relation to environmental, biodiversity and climate policies. This project will provide the first comparative empirical data on, and analysis of democratic reforms that expand
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Biomolecular Engineering ) and Professor Gregor Verbic (School of Electrical and Computer Engineering ), in partnership with industry collaborators. Your key responsibilities will be to: develop, implement, and
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Sciences, Political Sciences, Computer Sciences, or Engineering, with a strong track record (relative to opportunities) in research on disaster management, extreme contexts, and resilience including a body
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sampling missions design of machine learning systems for real-time obstacle detection, terrain analysis, and environmental adaptation in extreme environments implementation of multi-constraint optimisation
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literature searches using relevant databases, developing study protocols, preparing surveys/experiments, managing and cleaning datasets, data analysis using R, data visualisation, and reproducible workflows