293 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" "UCL" "UCL" Postdoctoral positions in United Kingdom
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Field
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* together with relevant experience. You will have a strong technical background in machine learning, especially RL and LLMs. An ability to work independently and as part of a collaborative research team is
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, cardiovascular diseases and rare diseases. This specific role focuses on engineering CAR-T cells and developing programmable gene control systems to improve safety and therapeutic efficacy. The successful
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the leadership of Principal Investigator Dr Andrew Siemion. Listen's interdisciplinary research has synergies with many of the department's research priorities, including exoplanet studies, machine learning
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folding. The ability to rapidly learn new techniques is highly desirable, and enthusiasm for working across disciplinary boundaries is essential. Full training will be provided where needed. Prior
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machine learning methods to model changes in the brain over the lifespan, including brain structure and function, and how those changes relate to environment and genomics. What We Offer As an employer, we
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, machine learning, or data analytics. As a proficient programmer (ideally Python), you will be curiosity-led, with exceptional communication skills, and thrive in a highly interdisciplinary environment. You
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disorder. Desirable criteria Experience applying advanced statistical or machine learning methods to complex datasets. Evidence of involvement in grant writing or development of independent research ideas
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and data processing skills: experience of programming in one or more languages (e.g. R, C/C++, Python, Matlab). Practical experience of algorithm development and implementation of machine learning
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machine learning methods to model changes in the brain over the lifespan, including brain structure and function, and how those changes relate to environment and genomics. About the Role The post is funded
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electrophysiology data obtained through collaborations and perform cross-species comparisons. We use machine learning techniques for neural data analysis and computational modelling with a special interest in