40 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" uni jobs at Imperial College London
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contribute to the development and enhancement of reporting tools and frameworks, utilising artificial intelligence and machine learning to maximise the use of data, while ensuring that data is accessible
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Machine Learning (ML) models to build a chemical ‘rule book’ for small molecule accumulation in bacteria. The position is available full time, starting in February 2026 (or as soon as possible thereafter
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(AI) and Machine Learning (ML) models to build a chemical ‘rule book’ for small molecule accumulation in bacteria. The position is available full time, starting in February 2026 (or as soon as possible
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clinical research groups at the National Heart and Lung Institute at Imperial College London applying statistical, machine learning and simulation approaches to combine experimental and clinical data with
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clinical research groups at the National Heart and Lung Institute at Imperial College London applying statistical, machine learning and simulation approaches to combine experimental and clinical data with
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, ideally applied to computational protein design, molecular modelling, or machine learning for biomolecular systems. Practical experience in molecular cloning, protein expression, purification, and
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postgraduate students, as well as postdoctoral staff in robotics and robot learning applications. The staff member will be required: To enable excellence in robotics research by providing expertise in
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. Alongside this, you will lead and develop the People Security Policy, manage key supplier relationships, and drive continuous improvement through effective governance, data, insight and learning across
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diverse areas transform the world for the better To deliver our events/programme, we work with staff across all departments and Institutes within Imperial, which creates extra opportunities for learning
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-supported and impactful for all participants. You will be responsible for the full lifecycle of the Career’s Service’s experiential learning schemes. These currently include Alumni Mentoring, Ask an Alum