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Field
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scholarship is suitable for students with a background in Engineering, Mathematics, and Computer Science. Students with interests in machine learning, deep learning, AI, intelligent decision making
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a growing field, with many applications in biomedical devices, electronics, and autonomous machines. Actuators to drive these robots utilise electronic, chemical, pressure, magnetic, or thermal
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Location: West Cambridge The world-renowned Cavendish Laboratory is seeking an enthusiastic, self-motivated student who enjoys working as part of a team to undertake a PhD in the NanoPhotonics Group
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Science, Soil Science or related disciplines who have/expect to graduate with a first/upper-second UK honours degree, or equivalent qualifications gained outside the UK. Funding details Funding is available
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Continuation of the award is subject to satisfactory progress. Number available To be confirmed by RADMA. Funding provider Research and Development Management Association (RADMA) Level(s) of study This funding
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and Health Data Science Mode of study: Full or Part-time study is possible Project Description: The successful candidate will work in a highly interdisciplinary environment as part of a vibrant cohort
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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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Science, Soil Science or related disciplines who have/expect to graduate with a first/upper-second UK honours degree, or equivalent qualifications gained outside the UK. Funding details Funding is available
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used in wind turbine blades, structural engineering exposed to offshore environments. However, the rapid growth of the wind turbine industry is expected to generate million tons of blade waste globally
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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders