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-assisted surgical task execution; Machine Learning (ML) for multimodal tissue characterisation for computer-assisted diagnosis and decision making. The post is funded by the CRUK grant “Cancer surgery at
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surgical navigation during robotic-assisted surgical task execution; Machine Learning (ML) for multimodal tissue characterisation for computer-assisted diagnosis and decision making. The post is funded by
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on a new project called TRUSTLINE, which is part of the Learning Introspective Control (LINC) DARPA Program. The project aims to develop machine learning (ML)--based introspection and monitoring
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, Neuroscience, Data Science, or a related health field with experience of working in clinical mental health settings. You will have a strong interest in AI and machine learning. Opportunity to contribute to a
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rig setups and the modification/re-purposing of existing rigs and equipment. Common activities include machining, cutting, water-jetting, welding, assembling and working with cabling and hydraulics
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. The Manipulation and Touch Lab investigates manipulation in humans and robots, haptic sensing, haptic interfaces and machine learning. More information may be found at: https://www.imperial.ac.uk
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that are embedded into routine health systems and data dashboards used to guide policy decisions. This role sits at the intersection of generative machine learning, statistical inference, geospatial analytics, and
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is funded by EPSRC, titled “Adopting Green Solvents through Predicting Reaction Outcomes with AI/Machine Learning”, involving academic investigators from 3 institutions (Imperial College London
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tools. In this role, you will mainly focus on strengthening our computational pipeline: integrating multiple standalone machine‑learning predictors into a unified, multi‑objective framework capable
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at industry-facing events. Strong technical and scientific knowledge in machine learning, preferably with experience in large language models (LLMs). Solid foundations in mathematics and engineering