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computational chemistry, reaction network analysis, and machine learning for organometallic catalytic reactions. 2. Design of membrane-permeable macrocyclic peptide drugs via machine learning structure
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principles but also capitalizing on research from various other subfields – educational psychology, sociology of education, design studies or computer science, and more recently, learning analytics and AI in
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of optimization and generalization to inform the design of practical training algorithms. To produce high-quality publications in top-tier machine learning conferences and journals. To offer guidance and assistance
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Job Summary: The Research Fellow will be responsible for undertaking in-depth research and innovation in machine learning, data science, and artificial intelligence on a novel urban intelligence
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, that can be realised using cloud compute infrastructure and other novel deployment architectures. Given our team's existing research skillset in novel machine learning approaches, we are recruiting a
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material intelligence can support a circular economy for space infrastructures. As a short-term feasibility study, we will design and populate a minimal, high quality database that links satellite components
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autonomous task execution and human-robot interaction. The successful candidate will work on cutting-edge research at the intersection of AI, robotics, and multimodal learning. Key Responsibilities Design and
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include deep learning, reinforcement learning, differentiable modelling and inverse design. You will implement and evaluate these methods using experimental optical systems and work towards their
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machine learning and AI acceleration. Perform performance, power, and area (PPA) analysis of processor and accelerator designs. Publish research findings in top-tier conferences and journals and contribute
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rare opportunity to work across the complete development chain of a medical device: from designing the sensors, through the readout electronics and data analysis, to integrating the system with robotic