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focused on the challenge of accelerating ternary neural networks using FPGA devices. The successful candidate will have significant experience in machine learning, FPGA design and an outstanding track
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ternary neural networks using FPGA devices. The successful candidate will have significant experience in machine learning, FPGA design and an outstanding track record in conducting machine learning research
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Diseases, School of Medical Sciences, Faculty of Medicine and Health. You will design in vitro and microfluidic-based model systems to evaluate vascular interactions related to medical device complications
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international research partnerships. The Postdoctoral Research Associate will design and conduct high quality restorative and reconstructive dentistry research. The incumbent will be supporting Dr Chun Xu and
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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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) design and simulate dynamic models of megaproject systems prepare and submit journal articles to high-impact publications contribute to competitive grant proposals and research impact activities
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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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UNSW Nuclear Innovation Centre. This appointment is one of up to six new postdoctoral positions in this research area for 2025. This position is best suited for candidates who have experience working
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where required. Participate in Implementation to Impact activities to support the growth of the program. Demonstrated experience in conducting applied health services research. Contribute to the design
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, thermochronology, tectonics, geodynamics, surface processes, relational database design, and geological data science. experience using GPlates, Underworld, Badlands, goSPL, Pecube, GLIDE, Age2Exhumation, and/or