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working with NLP in general and LLMs in particular. They will also help to further develop machine learning models to predict clinical outcomes. Familiarity with current methods in this area is essential
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health data, such as electronic health records or biobank-scale resources (e.g., UK Biobank, All-of-Us, FinnGen). Familiarity with machine learning approaches, such as penalised regression, deep learning
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health data, such as electronic health records or biobank-scale resources (e.g., UK Biobank, All-of-Us, FinnGen). Familiarity with machine learning approaches, such as penalised regression, deep learning
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from industry and research from Norway, Denmark, Belgium, Italy, Poland, Sweden, and Estonia. The appointment is duration of three years. During the evaluation process, priority will be given
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or machine learning methods Advanced knowledge of electronic healthcare records and their use in development and validation of risk prediction models Knowledge in application of econometrics in research
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To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD in health data science, medical statistics or machine learning methods
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Experience in human-centred design or user experience (UX) research in digital health Understanding of machine learning, AI, or big data analytics applied to health apps Experience working on NHS-funded
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to Medicine (Pharmacy, Nutritional Sciences and Women's Health cluster) for REF 2014 was rated as world-leading or internationally excellent. We use this expertise to teach the next generation of health
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satellites, and marine reanalysis products using machine learning to quantify CO2 uptake in the North Atlantic and the Nordic Seas. Clarify magnitude and causes of interannual variation in this CO2 uptake