10 postdoctoral-vision-deep-learning Postdoctoral positions at UNIVERSITY OF SYDNEY in Australia
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are seeking to appoint a Postdoctoral Research Associate (PDRA) to join a project researching global environmental changes and impacts on coral reef systems. The successful candidate will work under the
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coral reef ecosystem responses Base Salary $109,263 - $121,054 + 17% superannuation About the opportunity We are seeking to appoint a Postdoctoral Research Associate (PDRA) to join a project researching
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Job related to staff position within a Research Infrastructure? No Offer Description Opportunity to join Associate Professor Khoon Lim as a Postdoctoral Research Associate Full time, fixed term for 12
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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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of talented students, from all over Australia and has a large cohort of postgraduate research students and offers a vibrant and world class research environment. The School is currently seeking a Postdoctoral
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opportunity The School of Geosciences at the University of Sydney is seeking a Postdoctoral Research Associate - EarthBank. As part of the establishment of a new AuScope EarthBank Project node
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position within a Research Infrastructure? No Offer Description Full-time, fixed term opportunity for 12 months Exciting opportunity to be a Postdoctoral Research Associate in Cancer and Stem Cell Research
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disciplines including aerospace, combustion, design, fluid mechanics, materials, mechanical, mechatronic and robotics engineering. To learn more about the School click here . The Clean Combustion Group
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Researcher in FPGA-based AI Hardware Acceleration who has: strong experience in FPGA design, machine learning or a related field in the case of the Postdoctoral Research Associate, a PhD (or near completion
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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