199 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" Fellowship positions in United Kingdom
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policy relevance. Coordinate modelling activities across multiple projects and deliver high-quality outputs on time. Integrate new methodologies, including AI and machine-learning approaches
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on exploring what works and what doesn’t - in the care of people at the end of life. Learn more about the project here: NIHR Award Details. The study is led by Associate Professor Susie Pearce, who will also be
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on exploring what works and what doesn’t - in the care of people at the end of life: Learn more about the project here: NIHR Award Details . The study is led by Associate Professor Susie Pearce, who will also be
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operations. Process control: process modelling, control, and optimization, with applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process
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calculations; Experience with developing, training, and optimizing neural networks or other machine learning models. For this position we are targeting a salary corresponding to Level 4 Spine Point 28 - 30
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data to address priority questions in cancer care pathways, diagnostic delay, and treatment access. The role will involve advanced quantitative analyses, such as survival modelling, machine learning, and
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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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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 skills
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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