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of Informatics, Uni-versity of Oslo, and will be part of a growing research agenda at the intersection of epidemiology, statistical modeling, machine learning and public health data systems. The project aligns
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such as R, Python, Julia, etc. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in English Desired qualifications: Experience with research on epidemiological
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background in one or more of the following fields are required: Numerical solution strategies for PDEs Mathematical modelling. Furthermore, experience within machine learning, parameter estimation/inverse
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their doctorate at the time of appointment) to explore their science interests within an inclusive environment for active research, learning and service. NRC Herzberg will provide the experience, support and
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Desirable criteria Experience of advanced statistical and/or machine learning methods, such as longitudinal analysis methods, latent variables models, clustering algorithms, missing data and clinical trial
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of epidemiology, statistical modeling, machine learning and public health data systems. The project aligns with recent developments at the HISP Centre at UiO, which is expanding its long-standing DHIS2
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learning methods, such as longitudinal analysis methods, latent variables models, clustering algorithms, missing data and clinical trial analysis Strong publication record Experience in women and children’s
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will be adapted to the candidate’s background and the evolving needs of the center. Possible directions include the application of rock physics models, Bayesian inversion methods, and machine learning
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Responsibilities of the Post Conduct research and development on sign language recognition using computer vision and machine learning techniques. Lead the implementation of inference models suitable for mobile and
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physics models, Bayesian inversion methods, and machine learning algorithms in the electromagnetic context. Qualifications and personal qualities: Applicants must hold a master’s degree (or equivalent) in