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Field
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Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time-to-event analysis; and statistical machine learning in general. OCBE has numerous collaborations with
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analysis. Experience with the use of High Performance Computing facilities. Insight into a range of machine learning methods and ideas. You need to: Write an application where you clearly demonstrate
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, teams are adapting to significant technological advances accompanied by great volumes of incoming data. Such changes have the potential to improve capabilities in complex and uncertain conditions, but
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The PhD candidate will gain intensive knowledge in innovative processing protocols for complex mineral processing, column leaching, and mining site environmental science through hands-on experiments
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of molecular and biological materials using X-ray and neutron scattering. The main research areas are materials for photovoltaics, proteins in solutions and at the interfaces, and complex nano-structured
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using X-ray and neutron scattering. The main research areas are materials for photovoltaics, proteins in solutions and at the interfaces, and complex nano-structured materials. For more information, visit
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Uppsala University, Department of Information Technology Are you interested in developing new image analysis and machine learning methods for precision medicine and clinical decision support? Would
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collected in January 2025 aimed at capturing submesoscale flows and the mixing, stirring and water-mass transformations they generate. This PhD will lead the analysis of physical and biogeochemical data
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modeling, multilevel (random effects) modeling, and analysis of data from complex samples Experience with management and analysis of big data Experience with machine learning and related approaches (e.g
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will get the opportunity to: develop skills in design of protein probes targeting specific complexes; produce and purify proteins in Escherichia coli and HEK293 cell cultures; determine structures of