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Description Job description We are seeking a talented and creative researcher for a challenging and innovative project focused on developing the next generation of algorithms for high-speed super-resolution
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Job description We are seeking a talented and creative researcher for a challenging and innovative project focused on developing the next generation of algorithms for high-speed super-resolution
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sampling-based and reinforcement learning-based motion planning algorithms for multiple robotic arms in automotive manufacturing, including testing, performance evaluation in both simulation and actual
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We are looking for a Research Fellow to conduct the research for the project entitled “Manual Assembly Job Quality Inspection”. The role will focus on research and development of AI algorithms
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learning algorithms. We combine statistical methods with online reinforcement learning algorithms to develop reinforcement learning algorithms and inferential tools. The successful applicant will be expected
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and optimisation algorithms, focusing on their practical application in the context of the RaceEngineerAI project. Tasks include: - Developing models capable of simulating the behaviour of racing
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learning algorithms (Deep learning, Reinforcement learning, etc.); Proficiency in written and spoken English - essential for data analysis and communication with stakeholders Excellent oral communication
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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, train, and validate advanced computational models and machine learning algorithms tailored to complex datasets. Collaborate with multidisciplinary teams including biologists, engineers, and clinicians
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems