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in epidemiology, causal inference, genetic epidemiology, and machine learning. As a PhD candidate in the project, you will: Actively participate in group meetings, design statistical analysis plans in
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Publish in leading international journals Contribute to the work package on digital home follow-up Contribute in the cross-cutting work on analysis and theory development The position will also support
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, collaborative analyses across work packages Publish in leading international journals Contribute to the work package on digital home follow-up Contribute in the cross-cutting work on analysis and theory
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Norwegian health registries and population-based cohorts to study use, effectiveness and safety of medications and vaccines. Combined with access to advanced e-infrastructure, secure analysis platforms and
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project with Norwegian industry and both Norwegian and European academic partners. About the position We need a candidate who can work with programming and data-analysis on sea ice and sea ice interaction
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an important factor in the evaluation process and should be well documented in a teaching portfolio. The applicant should describe her/his qualifications in view of the Scholarship of Teaching and Learning (SoTL
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, or system analysis). Background in one or more of the following areas: Infrastructure or transport systems Risk, reliability, or resilience analysis Data analysis and computational modelling / programming
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influencing democratic perceptions and support. Focusing on political psychology, the project employs quantitative analysis to interrogate the relationship between authoritarian personality traits, populist
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(earthquakes, landslides, and other gravitational instabilities). Develop advanced numerical models for improving the simulation, the analysis, and the prediction of geohazards, as well as the application
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mechanisms of health and disease. Projects exploring biological questions, cellular processes, or precision medicine through the exploitation of integrative analysis of single-cell or spatial omics data