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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
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Australian or New Zealand citizens or Australian permanent residents newly enrolling in a PhD. Students undertaking the joint PhD program will be enrolled in a PhD at both institutions. Your supervisory team
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Engineering (ISSE) is one of the two computer science institutes at Clausthal University of Technology and is home to several research groups. You can find more information about the ISSE Institute on our
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responses. You will be using a game engine (Unity or Unreal Engine) connected to motion simulator chairs and a force feedback steering wheel to collect objective and subjective performance data as
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distinctions between valuable, acceptable, and non-acceptable use of these technologies in sport. The Nature and Value of Sport Virtual sports: With the help of virtual reality or computer-generated environments
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at the very top of our game in research, technology, and economics, they will. And while the highly-publicized wave of high-frequency or “flash” trading based on sheer speed of execution might have reached its
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top of our game in research, technology, and economics, they will. And while the highly-publicized wave of high-frequency or “flash” trading based on sheer speed of execution might have reached its
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experience in developing and applying computational intelligent, multi-agent systems and applied game theory techniques to address societal problems, and energy systems are an increasingly important