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for An enthusiastic, self-motivated, and resourceful candidate with a 1st or upper 2:1 degree in mechanical engineering, aerospace engineering, materials science, electrical engineering, or a related field. Desirable
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3-year PhD studentship: Scaling-Up Functional 3D Printing of Devices and Structures Supervisors: Professor Richard Hague1 , Professor Chris Tuck1 , Dr Geoffrey Rivers1 (1 Faculty of Engineering) PhD
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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addressing the behaviour of thin foil materials for aerospace forming applications. The successful candidate will have a first-class or upper second-class honours degree in mechanical engineering or a related
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these robots utilise electronic, chemical, pressure, magnetic, or thermal mechanisms, with the current generation having significant drawbacks, including low energy efficiency, high operating voltage
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leverage advanced bespoke continuum robotic systems to demonstrate the feasibility of applying the proposed coatings can be deployed in-situ. Ultimately, this work bridges the gap between the theory
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salary) for 3 years An additional £2,000 per annum for consumables and travel Requirements The candidate should have a 1st or high 2:1 degree in electrical/mechanical engineering, physics, mathematics
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Eng at Nottingham https://www.nottingham.ac.uk/coatings/ is an international reference for all Cold Spray based activities. BAE systems provide some of the world's most advanced, technology-led
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of the GAG biosynthetic machinery Applying novel GAG analytical technologies to investigate how changes in GAG structure and organisation drive and/or respond to shifting developmental stages. Working
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/or dynamic analysis of mechanical/robotic systems •Ability to use finite element modelling and to simulate complex mechatronics •Ability to implement control and kinematics with hardware-in-the-loop