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/ . The post offers an exciting opportunity for conducting internationally leading research on the whole spectrum of novel machine learning algorithms and practical medical imaging applications, aiming
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Applications are invited for a Research Associate* position in the intersection of machine learning and information theory. The successful candidates will be based within the Information Processing
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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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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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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
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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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vision, natural language processing (NLP), and audio processing. Prior experience in machine learning, computer vision, or NLP is essential. A strong track record in multi-modal learning or related fields
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.). Besides these research-focused areas, we expect the successful candidate to be able to contribute to our teaching portfolio within e.g., data science, machine learning, IoT, computing, etc. We additionally
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expected to initiate and expand research collaborations with colleagues at the School, at Imperial College London, and beyond. Teaching – The Dyson School of Design Engineering provides exceptional learning
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and computer-intensive resources. Performance Optimization: Continuously monitor and optimize the performance of both internal and cloud-based systems, implementing best practices for resource