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A PhD studentship awarded by the Freeman Air and Space Institute (FASI) to support the Institute’s research and capacity building work in the field of air power. Award details In an increasingly
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select ‘Create a Postgraduate Application’. Use ‘Course Search’ to identify your programme of study: search for the ‘Course Title’ using the programme code: 8060F select ‘ PhD Electrical and Electronic
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Exciting Fully Funded PhD: Computational Modelling for High-Pressure, Low-Carbon Storage Technologies. Be a Key Player in Shaping the Future of Clean Energy Storage! School of Mechanical, Aerospace
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dissertation supervision. For this T&S role, you must have a PhD in a relevant subject (or a PhD near completion – i.e. strictly within three months of submission), and a strong scholarly profile or trajectory
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of researchers who conduct cutting-edge research into NLP and AI within the University of Cambridge. Education: An excellent first degree in computer science, engineering or a closely related field Skills and
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Engineering, Computer Science or related disciplines. Experience in autonomous system, manufacturing/robotics and machine vision development will be an advantage. To apply please contact the supervisor, Dr Kun
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the level of Security Check (typically known as “SC”) which includes having a minimum of five years permanent residency in the UK. Programme and Location: The Engineering Doctorate Researcher will
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research activities. The applicant will have obtained or be close to obtaining a PhD in Mechanical Engineering or Materials Science. Appointment at Research Associate level is dependent on having a PhD
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PhD Studentship: Artificial Intelligence for Building Performance – Optimising Low-Pressure Airtightness Testing Supervisors: Dr Christopher Wood (Faculty of Engineering) and Dr Grazziela Figueredo
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to how well they meet the following criteria: A first class or strong upper second-class undergraduate honours degree in Engineering, Mathematics, Computer Science or Physics Excellent English written and