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of robotic equipment within bespoke cells to improve the efficiency and performance of machines. Provide guidance, assistance and technical advice with programming and integration of associated software and
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of Sheffield. The role is part of a programme of research that is fully funded by the Aerospace Technology Institute (ATI) in a large collaborative programme with several Industry partners, including Airbus
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an interdisciplinary supervisory team and an established Advisory Programme. The student will join the well-funded and friendly Whitfield lab (see blog). Please apply for this project using this link: https
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that the selection process will take place in August 2025. This will consist of a presentation, an activity and an interview. We plan to let candidates know if they have progressed to the selection stage within two
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to plan own workload and prioritise conflicting deadlines Essential Application/Interview/Presentation Ability to make decisions and apply creative approaches to solving complex technical problems Essential
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Ability to plan own workload and prioritise conflicting deadlines Essential Application/Interview Ability to make decisions and apply creative approaches to solving complex technical problems Essential
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solving (Application form, Interview) Experience of developing and maintaining financial systems (Application form, Interview) Ability to assess and organise resources, and plan and progress work
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reports, etc.). Plan and prepare papers for journals/presentations at national/international conferences to disseminate research findings. Read academic papers and textbooks, and attend conferences, to keep
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biomechanical computational model, and have some experience in scientific programming such as Python. You will join the group of Dr Xinshan Li, Professors Damien Lacroix and Enrico Dall’Ara, as part of
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. Essential Application & Interview Significant experience in high-fidelity simulations of turbulent flows, high-performance computational methods and programming. Essential Application & Interview Unique self