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amounts of data required for effective monitoring. This data-driven approach can result in high costs, increased computational demands, and logistical challenges in data storage and processing. A crucial
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PhD Studentship: A continual learning approach for the development of robust robotic control systems
. AI is expected to be at the centre of these systems, being the foundation of computer vision, monitoring, and control solutions. Despite the promising results that AI (and especially Deep Learning) has
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are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in on-platform manufacturing engineering. The successful candidate will be based at the Rolls-Royce
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simulations and computer-aided design, as well as training in more general training in scientific communication, project management, collaborative working, and mentoring and leadership. All these skills
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academic background in one or more of the following areas: Electrical and Electronic Engineering, Aerospace Engineering, Computer Science (with a focus on AI/ML or systems modelling) with good electrical
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mapping of sites and X-ray Computed Tomography of soil samples. Full training will be given for all aspects of the work and strict health and safety protocols will be followed at all times. Keyword Search
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, Physics, Computer Science or similar Enthusiasm for hands-on experiments Basic coding abilities in any language (e.g. Python or MATLAB or C/C++) Excellent communication skills The ability to work
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the research environment for PGRs. PGRs benefit from training through the Researcher Academy’s Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed
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. Applicants should possess a first-class or upper-second-class honors degree in Aerospace, Mechanical, Electrical, Electronics, or Communication Engineering, Physics, Mathematics, Computer Science, or a related