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of Oxford. The post is funded by United Kingdom Research and Innovation (UKRI) and is for 24 months. The researcher will develop 3D mapping and reconstruction algorithms with relevance to mobile robotics
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LEO, MEO, and GEO constellations), and complementary on-board sensors. Research will investigate algorithms for robust multi-sensor fusion and positioning assurance. A strong emphasis will be placed
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, despite its widespread application, polygraph data capture and analysis has received limited systematic research and does not yet incorporate modern sensors, computing and analytical techniques. Project
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data are needed to enhance our understanding of sources, pathways and impact of litter. Cefas is developing a visible light (VL) deep learning (DL) algorithm and collected a large 89 litter category
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across Scotland’s west coast. It will evaluate the practicality of different image capture techniques and the potential of different sensor types (e.g., RGB, multispectral) to generate beach litter images
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Refine the pressure-sensing system, calibration and control algorithms Contribute to the durability testing and validation to meet ICU clinical standards Collaborate with a multidisciplinary team of
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physiological signals associated with bruxism in real-time. The successful candidate will focus on: Developing and refining novel wearable sensors that are flexible, comfortable, and capable of capturing subtle
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Model Based Design and Flight Testing of a Vertical Take-Off Vertical Landing Rocket (C3.5-MAC-John)
tested will have applications for landing on other planets or moons, or even propulsive landing of rocket stages on Earth. These missions require the use of novel guidance algorithms, sensors, and control
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qualifications include: 1) experience implementing Simultaneous Localisation and Mapping (SLAM) algorithms; 2) familiarity with sensor-based navigation and field trials of mobile robotic systems. For more
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. Successful re-development for end-of-life composites could enable reuse in other structural applications. This PhD will investigate the development of hierarchical Bayesian algorithms to capture