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experience of treatment. The overarching aim of the project is to use machine learning methods to understand why many people who are referred for treatment will drop out prematurely. To do this, two studies
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of acoustic wave propagation in moving fluid and physics-based machine learning (ML) methods. Support experimental design in the laboratory, carry out data processing and to use the experimental results
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). Modelling tools used will vary according to application but are likely to including process simulation using Population Balance Modelling, DEM simulations and Machine Learning Approaches. Main duties and
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science, computer vision, medical/image analysis is essential. Experience of research (or interest in) in one or more of the following: deep learning; big data management; computational pathology; medical imaging
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. To fill in this gap, in collaboration with industrial partners, the research will develop novel Machine Learning and Computer Vision methods for detecting and localising. These will be used to develop
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/interview) A degree (Bachelor’s, Master’s, or PhD or equivalent experience) in Software Engineering, Computer Networks, Embedded Systems, AI, Data Engineering, or a related subject (assessed at: application
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collaborative programme of research funded by the Aerospace Technology Institute (ATI) with several Industry partners, including Airbus, GKN and Renishaw. Critical for the implementation of additive manufacturing
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are looking for someone with a strong interest in developing novel, unconventional computing systems to tackle complex machine learning tasks at low energy. You should hold a PhD, or be close to submitting, in
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of Computing at Imperial College London in 2022. Personal website：https://cherise215.github.io/ About the School/Research Group The successful candidate will join the Computer Vision group in the School
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AMRC marketing teams Programme Administration & Support Be the point of contact for students and supervisors, and provide guidance and support on matters related to the PhD and EngD programmes Support