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into practical performance solutions. The “Travel, sleep and fatigue optimal management for long-haul performance” PhD programme will focus on mitigating circadian and travel fatigue challenges associated with
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organisation, are often based on data derived from elite football players; tasks requiring very different physical, physiological, and cognitive demands, performed by a very different population. Whilst
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multidisciplinary research in energy markets, optimization, game theory, and machine learning. Our team of 13 members (link ), from 10 different nationalities, values diversity and includes experts from a range of
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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The Biased Blame Game - Understanding why we blame others for our own mistakes in cooperative settings Dr Paul Rauwolf Applications are invited for a fully funded 3-year PhD studentship under
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discipline, complete an expression of interest (EOI). The steps are: Complete the EOI available at Next Generation Graduates Program (NGGP): Sports Data Science & AI - Centre for Data Science Peruse
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Requirements: Computer Engineering, Gaming Engineering or similar. Knowledge and Professional Experience: AI programming based on Python, Auto_Script, Machine and Deep learning and computer vision. To have
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Embark on a ground-breaking PhD project harnessing the power of Myopic Mean Field Games (MFG) and Multi-Agent Reinforced Learning (MARL) to delve into the dynamic world of evolving cyber-physical
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We are looking for a doctoral candidate with a strong computational, engineering, data scientific or machine learning background that is keen to work in an interdisciplinary environment and open to
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Computer Science, Economics, FinTech and Financial Innovation, Mathematics, or a related field from the University of Cape Town. Strong background in game theory, mechanism design, microeconomics, or cryptographic