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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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science, along with proven skills in prototyping software using real-time 3D engines and implementing machine learning models. With 50+ researchers and PhD students, the Centre for Sustainable Cyber Security (CS2
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Section 1 - Project Details: Studentship Start Date: 22/09/2025 Principal Supervisor Name: Julia Reiss Julia.reiss@brunel.ac.uk Other Contacts: Thomas Miller Thomas.miller@brunel.ac.uk Project Description: Freshwater ecosystems face increasing stress from pharmaceutical pollution and climate...
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departments and research centres in the School of Policy and Global Affairs, offering potential for interdisciplinary research in politics, sociology, or criminology. About the programme Upon joining our PhD
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BCAST Applications are invited for one full-time EPSRC Industrial CASE (ICASE) PhD studentship for the project “Development of high performance and highly impurity-tolerant recycled Al alloys
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simulation regimes by harnessing and advancing the latest developments in AI Machine Learning. This studentship is a continuation of prior work that is looking at using new cutting-edge deep learning models
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Salary The studentship will cover full tuition fees at the Home (UK-based) student rate and a maintenance grant for 3 years, at the rate of £21,237 pa. A funded PhD position is available on a
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Matthew Santer, m.santer@imperial.ac.uk For queries regarding the application process, please contact: Lisa Kelly, PhD Administrator, l.kelly@imperial.ac.uk You can also learn more about Imperial at
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Award duration: 4 years Food processing currently relies heavily on the combustion of natural gas to provide process and space heating. Until recently, natural gas was considered the preferred fuel for heating due its lower unit cost and greenhouse gas emissions compared to alternative fossil...
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Appropriate computational skills and knowledge of programming languages (Python, C++, etc.) Experience with Machine and Deep Learning models and software (Keras, Scikit-Learn, Convolutional Neural Networks, etc