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Field
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the performance of novel, renewable, wave energy harvesting approaches. Here the research ambition is to extend the state of art from small scale sensor networks (nW’s to mW’s), towards a vehicular scale (W’s to
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analytical and numerical skills, with a well-rounded academic background. •Demonstrated ability to develop precision mechanical devices and mechatronics •Ability to develop kinematic and/or dynamic analysis
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-rounded academic background ◾Demonstrated ability to develop precision mechatronics system and algorithms ◾Ability to develop kinematic and/or dynamic analysis of mechanical/robotic systems ◾Ability
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from being part of a dynamic, focused and professional study environment and all become valued members of the Cranfield Doctoral Network. This network brings together both research students and staff
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will use advanced unsteady computational fluid dynamic methods for the analysis of coupled intake/fan configurations in crosswind and high-incidence conditions. The research will adopt these methods
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have partnered with AWE to fund a 4-year Computational Project to use state-of-the-art Computational Chemistry techniques to understand structure-property relationships in oxide scintillators. We will
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the successful candidate embarking on a PhD programme at LSHTM. It is anticipated that the role will lead to a further 18 month funded opportunity at Max Planck Institute for Demographic Research (MPIDR), in
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A position exists, for a Research Assistant/Associate in the Department of Engineering, to work on Data Science for Construction Productivity. The researcher's responsibilities will include
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The Centre for Advanced Powertrain and Fuels (CAPF) at Brunel University of London invites applications for a Research Assistant / PhD position as part of an EU MSCA Doctoral Training Grant
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The Centre for Advanced Powertrain and Fuels (CAPF) at Brunel University of London invites applications for a Research Assistant / PhD position as part of an EU MSCA Doctoral Training Grant