37 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Ulster University" uni jobs at Imperial College London in United Kingdom
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and verbal. Strong organisational and time-management abilities. Confident in using databases and learning bespoke systems. Ability to triage and respond appropriately to emotionally sensitive or urgent
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programmes. We are looking for a sessional lecturer to teach a practical option in Digital Media Campaigning. Imperial is committed to providing an educational experience that empowers graduates to be leaders
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-edge projects in chemical biology and drug discovery and will underpin the development of state-of-the-art Artificial Intelligence (AI) and Machine Learning (ML) models with collaborators. You will
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We are seeking to appoint a postdoctoral research associate in Machine Learning and Chemometrics for Antimicrobial Resistance for 18 months. The successful candidate will carry out research
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will support the generation of high-throughput mass spectrometry (MS) data to power state-of-the-art Artificial Intelligence (AI) and Machine Learning (ML) models to build a chemical ‘rule book’ for
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of people who are dedicated to helping young people innovate through hands-on learning experiences. The workshop has a variety of tools from 3D printers and laser cutters to sewing machines and woodworking
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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