42 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"University-of-Chester" positions in United Arab Emirates
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primarily research on Reinforcement Learning, and/or Optimal Control, and/or Model Predictive Control. RISC invites qualified applicants in the areas of electrical, computer, or mechanical engineering, or
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main PhD focus) such as additive manufacturing, advanced/hybrid manufacturing, machine learning, artificial intelligence, computer vision, robotics, UAVs, etc. is a plus. Other preferred qualifications
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following: Data Science, Machine Learning, Computational Social Science, Big Data. Relevant skills could include statistical analysis, data management and collection, causal inference, network analysis, graph
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and expertise in their field. The position requires experience with at least one of the following: Data Science, Machine Learning, Computational Social Science, Big Data. Relevant skills could include
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and expertise in their field. The position requires experience with at least one of the following: Data Science, Machine Learning, Computational Social Science, Big Data. Relevant skills could include
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collaboratively within a team. Applicants must have a PhD, or equivalent advanced or terminal degree from a recognized institution of higher learning, in materials science and engineering, chemical engineering, or
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to discuss project developments and thus learn from, support, and brainstorm with their peers in diverse disciplines. Finally, Fellows will submit a brief narrative report of their fellowship activities
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that the candidate has prior research experience in one or more of the following research topics: Free space optical communication Visible light communication DSP for coherent optical communication Machine learning
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-curricular learning, and wellbeing. You will work closely with Head of Student Life to deliver engaging student programming and services with the aim to foster an inclusive community. This includes planning
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models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation through computer simulations and/or experimental