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developments in machine learning (ML) for phase retrieval. This project is a collaboration with the Ada Lovelace Institute and Diamond Light Source. If you are interested, please contact the supervisor for more
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Supervisory Team: Hector Calvo-Pardo; Vahid Yazdanpanah; Tiago Alves (Solar Americas ); Enrico Gerding PhD Supervisor: Hector Calvo-Pardo Project description: Machine learning (ML) holds immense
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Project title: Using machine learning to evaluate atomic force microscopy nanoindentation data Supervisory Team: Dr Martin Stolz, Dr Sasan Mahmoodi Project description: The University of Southampton
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Engineering. In addition to the research project outlined below you will receive substantial training in scientific, technical, and commercial skills. This project looks at efficient quantum machine learning
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traces and diagnosis from medical signals such as EEG/ECG all involve data observed over time. Time series machine learning (TSML) [1,2,3,4,5] offers the potential to contributing to a huge range of
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algorithms to combine information from the two modalities. Utilising the latest advances in machine learning, the project aims to overcome two fundamental challenges, 1) the identification of the unknown
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PhD Supervisor: Antonia Marcu Supervisory Team: Antonia Marcu, Jonathon Hare Project description: Deep Learning (DL) is a widely successful tool. However, there are many fundamental challenges left
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University Guide 2022) within the University of Southampton which is ranked in the top 1% of universities worldwide. The successful candidate must have a strong background in machine learning. Prior knowledge
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Supervisory Team: Dr Christine Evers Project Description: Are you keen on conducting research at the intersection of artificial intelligence, deep learning and robot perception? We are recruiting a
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the UK. If you like learning and applying novel concepts using the latest technology, you will certainly enjoy working with us. During your PhD studies you will have the opportunity to learn how to design