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members of staff. Research in the Department is organised into six themes : Causality; Computational Statistics and Machine Learning; Economics, Finance and Business; Environmental Statistics; Probability
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to develop your knowledge and skills on autonomous cubesats with impactful applications in planetary defence. You should have a PhD (or near completion) in space engineering, computer science or an equivalent
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European Centre for Environment and Human Health in the Faculty of Health and Life Sciences at the Penryn Campus in Cornwall. Measures taken in the built environment to reduce energy consumption
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: • Experience with programming (Python, MATLAB), • background in aerospace, computer science, robotics, or electrical engineering graduates, • hands on skills in implementation of fusion
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, which is not possible with current systems. It aligns with key STEM themes and EPSRC’s strategic focus on ‘Engineering’, ‘Health and Medical Technologies’, and ‘AI, Digital, and Smart Applications
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honours degree in materials science, physics, engineering, or a related discipline. The ideal candidate will be self-motivated, with an interest in both computational modelling and practical manufacturing
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but not essential. A strong background in materials science and/or modelling is essential. Experience in machine learning, computer vision, and computer programming is desirable. In addition
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Engineering, Faculty of Engineering and Applied Sciences, Cranfield University, in the area of performance simulation, analysis, and optimization of supercritical CO2 power generation systems. Cranfield has
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stakeholders. Demonstrated ability to manage iterative feedback cycles and refine deliverables accordingly. The skills, qualifications and experience required to perform the role are: A PhD in Computer Science
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, to discuss the project or if you have any questions. Entry requirements: Applicants should have, or expect to achieve, at least a 2:1 bachelor’s degree (or equivalent) in biomechanics, sport science