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Field
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reusable launchers, autonomous robotics, and advanced materials could redefine how we design space structures. The ability to remotely assemble orbital systems from multiple launcher payloads would allow
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the foundation of computer vision, monitoring, and control solutions. However, real applications of AI have typically been demonstrated under highly controlled conditions. Battery assembly processes can be
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-efficient research that prevents fatigue failures has pushed towards integrated computational materials engineering approaches that improve competitiveness. These approaches rely on physics-based models
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an original programme of research working with ecologists Dr Ashley Lyons and Dr Anne Oxbrough in collaboration with Dr Steven Ewing at the RSPB Centre for Conservation Science. This PhD is part of the Cumbria
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. Built from compliant, flexible materials, the soft robotic arm will be designed to traverse tight bends, junctions, and variable diameters commonly found in pipeline networks and facility internals
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changes (so called swelling). Swollen batteries are at risk of rupturing which may significantly shorten their lifetime. Development of advanced computer models is critical for understanding and
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Applications are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in manufacturing engineering. The successful candidate will be based
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, participants, materials/apparatus (if appropriate), procedure, analyses References. Please see the Guidelines for Applicants (music education) at www.rncm.ac.uk/research/programme/postgraduate for further
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research focuses on Materials physics, Quantum technology, Soft & living matter, and Advanced energy solutions. Topics extend from fundamental research to important applications. We educate future
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through advanced cooling integration, as well as using topology optimisation, soft magnetic materials (e.g., cobalt-iron alloys), and additive manufacturing to push performance boundaries. The research will