62 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" positions at Imperial College London
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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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, 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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(ECRI), you will play a vital role in delivering high‑quality learning, development and support activities that empower Imperial’s early career researchers. Working as part of a collaborative and dynamic
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Bruce. Learning opportunities: You will develop an expertise in the aero-thermo-structural simulation and optimisation of hypersonic vehicles. Professional Development: You will have access to engaging
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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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support, and manage the safe operation of shared equipment areas as well as supporting tours and VIP visits. You will also onboard and induct all new clients, helping them to learn how to use state
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, learning, research and student experience across all campuses, working with senior academic and Professional Services colleagues to optimise utilisation, planning and readiness for future growth. You will
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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