192 machine-learning-"https:"-"https:"-"https:"-"https:"-"UCL" Fellowship positions in United Kingdom
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to the project’s scope, such as mechanistic interpretability of LLMs, robustness verification of machine learning models, and conformal inference. Applicants should demonstrate scientific creativity, research
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Introduction As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill
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to the project’s scope, such as mechanistic interpretability of LLMs, robustness verification of machine learning models, and conformal inference. Applicants should demonstrate scientific creativity, research
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not yet competitive for 5-year clinician scientist fellowships. This post is designed for applicants with a research interest in machine learning or data science approaches for patient stratification
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. Coordinate modelling activities across multiple projects and deliver high-quality outputs on time. Integrate new methodologies, including AI and machine-learning approaches, into simulation design. Conduct
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developing machine learning or data science approaches for patient stratification and genetic association analyses using cardiac magnetic resonance imaging in biobank populations. Successful applicants will
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implementing the Grade 11 module of ICCS, examining civic learning among older adolescents, particularly in vocational education pathways. You will engage in international comparative research, applying advanced
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expertise in a supportive and innovative environment. In this role, you will lead the computational strand of the project, applying molecular simulations, data analysis, and machine learning to uncover how
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researchers on 5G testbed operation, integration and performance testing. Job Requirements Bachelor’s, master's or Ph.D. in Electrical and Computer Engineering, Computer Science or related field. Solid
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- Salary Sacrifice Car Scheme (Tusker) - Salary Sacrifice Cycle Scheme - Salary Sacrifice Home & Tech Scheme - Life Assurance Full details on our employee benefits can be found on our careers page