30 algorithm-development-"Prof"-"Prof"-"Washington-University-in-St" positions at UNIVERSITY OF SYDNEY
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-based algorithms (e.g., GNNs, deep reinforcement learning) design and simulate dynamic models of megaproject systems prepare and submit journal articles to high-impact publications contribute
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learning at scale. Research directions include designing algorithms and methods for adaptive and personalised feedback, modelling learning behaviours with sequence and deep learning methods, and generating
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developing targeted therapies that eliminate these treatment-resistant cells. Cancer stem cells are increasingly recognised as key drivers of tumour growth, relapse, and resistance to conventional therapies
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that transforms lives. The Lab's work is community centred, multidisciplinary, exploratory and applied. To kickstart a new ecosystem of public policy research and development, our projects build on deep
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trust survey informed by current academic literature. This role will work with third-party platforms such as Qualtrics to support the distribution of the survey and assist in developing appropriate sample
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largest division of the University of Sydney, and is dedicated to attracting and developing the brightest minds in health education and research to make and shape the future of health. Sydney Local Health
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developing the brightest minds in health education and research to make and shape the future of health. Sydney Local Health provides a diverse range of public healthcare to more than 740,000 people living
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applies and develops their expertise in conducting research to further the Faculty or School's research agenda. They conduct research and/or scholarly activities under the limited supervision of senior
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1856 the Sydney Medical School has been dedicated to developing caring, clinically outstanding, research-capable and globally aware graduates who have the capabilities to become leaders in medicine
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the project prepare materials for publications in journals and conferences collaborate with industry partners and leaders in the field of FPGA-based machine learning accelerators About you The University values