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surgical navigation during robotic-assisted surgical task execution; Machine Learning (ML) for multimodal tissue characterisation for computer-assisted diagnosis and decision making. The post is funded by
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intelligence; can present at national and international conferences; and prepare manuscripts as first or joint author for submission to leading journals and conferences in machine learning, cancer research and
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Vision, Robotics, Evolutionary Computation, Deep Reinforcement Learning, and Machine Learning. This should include a proven publication track record. You should also have: Research Associate: A PhD (or
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-of-concept of such systems and have a practical understanding of: Signal processing algorithms, Security and Privacy Antennas and RF sensing Machine learning for communications systems Integrated Sensing and
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Contribute to the supervision of junior researchers and students as opportunities arise A PhD in a relevant quantitative discipline (e.g. mathematical modelling, geo-statistics, machine-learning) Experience
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is funded by EPSRC, titled “Adopting Green Solvents through Predicting Reaction Outcomes with AI/Machine Learning”, involving academic investigators from 3 institutions (Imperial College London
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Transport Systems Laboratory, equipped with cutting-edge technology that supports research in autonomous transport, decarbonisation, machine learning, travel behaviour, air transport management, and transport
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understanding of: Signal processing algorithms, Security and Privacy Antennas and RF sensing Machine learning for communications systems Integrated Sensing and Communications You will enjoy adventure in research
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tools. In this role, you will mainly focus on strengthening our computational pipeline: integrating multiple standalone machine‑learning predictors into a unified, multi‑objective framework capable
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the environment of a large international science collaboration Familiarity with machine learning techniques For a full list see the job description The opportunity to continue your career at a world-leading