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for research leadership. Strong experience in at least two of the following areas: reinforcement learning machine learning, deep learning dynamic scheduling, optimisation and control Experience in developing
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), psychophysical methods, computational neuroscience methods, machine learning and modelling. Our studies utilise various haptic devices, and mechanical and electrical stimulators. Key skills required: PhD
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and support clinical learning and teaching across the School of Clinical Medicine. The role reports to Head of Discipline and has no direct reports. Key skills required: A medical degree, preferably
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nonautonomous dynamical systems, spectral analysis, machine learning, data-driven dynamics, stability/perturbation theory/rigorous numerics. Possible applications of the new theory include the analysis
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of innovative machine learning methods. The Senior Research Associate will drive the direction of research within this broad area and collaborate with others in the ARC Centre of Excellence for Weather of
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strong sense of community & inclusion Enjoy a career that makes a difference by collaborating & learning from the best At UNSW, we pride ourselves on being a workplace where the best people come to do
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licence is essential. Car ownership is desirable. To learn more about this position, and view the comprehensive skills and criteria list, a copy of the Position Description can be found by clicking
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/photovoltaic-and-renewable-energy-engineering/our-research/research-activities/characterisation-defects-machine-learning Skills & Experience: A PhD in Computer Science or a related field. Thorough theoretical
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developments in scientific machine learning, which blends data-driven learning and physics-based modelling. The whole project will make a significant contribution to uncertainty quantification, and should
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Communications, e.g., beamforming, transceiver design Semantic/goal-oriented communications Machine learning-based ISAC New waveforms and multiple access schemes, e.g., NOMA, OTFS, etc. THz communications and/or