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occupational traffic safety, with a focus on the car driving behavior of employees who drive as part of their job but are not professional drivers. Lack of knowledge, training, stress, fatigue, and poorly
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if you have worked with prediction models, machine learning or AI models and are familiar with blood cells such as neutrophils, leukocytes and platelets. Work experience in the area is meritorious. If you
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machine learning techniques into a modern AI planning system. The project will involve both theoretical and experimental work As a PhD student, you devote most of your time to doctoral studies and the
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Uppsala University, Department of Information Technology Are you interested in developing new image analysis and machine learning methods for improved cancer understanding, diagnostics, and
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Sciences division. This multidisciplinary team utilises a combination of machine learning and mechanistic modelling to derive models and scientific insights from data, which both support and enhance drug
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of MSI advances our understanding of complex brain processes. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection to generative models such as
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. Rocío Mercado Oropeza, applies machine learning to molecular engineering problems in life sciences and drug discovery, and is based in the Division for Data Science and AI within the CSE Department
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Wiberg is “Innovative statistical and machine learning methods for comparing performance and outcome in register data studies”, with overall aim to develop, evaluate, and implement innovative statistical
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environmental factors. Findings will be further explored through bioinformatic methods. Other techniques may include machine learning and mathematical modeling. Additional tasks within the research group may also
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multimodal machine learning. Admission requirements The general admission requirements for doctoral studies are a second- cycle level degree, or completed course requirements of at least 240 ECTS credits