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mobile robotics, you will manage own academic research and administrative activities, adapt existing and develop new methodologies in robotics, design working algorithms from theories, deploy and test
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with MoniRail Ltd and Durham University. The primary focus will be on designing and implementing deep learning and anomaly detection algorithms to analyse large-scale, real-world sensor data collected
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collaboration between the OU and Teledyne e2v (T-e2v), a world-leading manufacturer of scientific and industrial image sensors. The CEI is dedicated to conducting research into advanced imaging technologies
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of fingers, the shapes of the fingers, and the positions of tactile sensors), and the control policy for that hand, when given a particular task or set of tasks. Through this, we aim to develop a framework
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optimise the robot hand design (e.g. the number of fingers, the shapes of the fingers, and the positions of tactile sensors), and the control policy for that hand, when given a particular task or set of
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filtering, target detection, tracking and classification. Evaluation of algorithm performance across environmental conditions is needed to quantify uncertainty and allow confidence in decision making. Sensor
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transmission methods (wired or wireless) will be optimised for robust data capture in natural sleep environments. AI-Driven Analysis: Develop advanced AI algorithms to analyse the collected sensor data, aiming
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and Durham University. The primary focus will be on designing and implementing deep learning and anomaly detection algorithms to analyse large-scale, real-world sensor data collected from in-service
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, advanced materials, and sensor development, while also addressing key robotic challenges such as real-time process monitoring and diagnostics in inaccessible or hazardous environments. We have discussed a
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building a UAV capable of quantifying aerosol size, composition and radiative effects in the Upper Troposphere-Lower Stratosphere (UTLS). Lead the selection, integration, and testing of advanced sensors