30 machine-learning-"https:" "https:" "https:" "The Open University" Postdoctoral positions in Norway
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on intelligent observing systems using machine learning and data assimilation methods in the ACTIVATE project. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/289326
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to observe next. By combining Bayesian inference, probabilistic modeling, and machine learning, the project aims to make Arctic observations more efficient, intelligent, and impactful. You will integrate field
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measurements are most informative and guiding where, when and how to observe next. By combining Bayesian inference, probabilistic modeling, and machine learning, the project aims to make Arctic observations more
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computational modeling to identify bacterial strains and metabolites that promote or hinder probiotic establishment. By combining multi-omics data with systems biology and machine learning approaches
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of Norway through the “Arctic MSCA-PF program”. Successful postdoc candidates will be invited for a two-day MSCA-PF symposium June 10-11, 2026 (hybrid physical/digital event, see details at https://uit.no
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through the “Arctic MSCA-PF program”. Successful postdoc candidates will be invited for a two-day MSCA-PF symposium June 10-11, 2026 (hybrid physical/digital event, see details at https://uit.no/arcticmsca
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event, see details at https://uit.no/arcticmsca/programstructure ). At this event, the candidates will present their past research achievements, discuss future plans with their potential supervisor and
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physical/digital event, see details at https://uit.no/arcticmsca/programstructure ). At this event, the candidates will present their past research achievements, discuss future plans with their potential
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future plans with their potential supervisor and learn how to write a successful MSCA-PF application. The selected candidates will, jointly with the supervisor, write the MSCA-PF application by
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, see details at uit.no/project/arcticmsca/program-structure ). At this event, the candidates will present their past research achievements, discuss future plans with their potential supervisor and learn