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% teaching component. The Department teaches in all the sub-fields mentioned above. The successful candidate will be part of the Faculty’s PhD programme. The work is expected to lead to a PhD in political
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data—into interpretable spatiotemporal risk models. A key methodological component could be the use of INLA for efficient inference in latent Gaussian models, and the candidate will contribute
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Analysis of Products) and experimental protocols for kinetic investigations in heterogeneous catalysis. Specific work tasks will include: Integrating various commercial and home-built hardware components
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and some familiarity with the preparation of tissue sections Experience working with tissue sections or organoid samples for bio-imaging applications Familiarity with image analysis tools such as MATLAB
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CO₂ emissions, and enhance resource efficiency. A DPP, serving as a core data element of the circular economy, is a publicly accessible record that provides information about a product’s lifecycle to
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• Experience with bioinformatics • Familiarity with high-throughput sequencing data and genome analysis. • Excellent written and spoken English skills, see requirements: https://www.mn.uio.no/english
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-tenured term of 4 years, and has a 25% teaching component. The Department teaches in all the sub-fields mentioned above. The successful candidate will be part of the Faculty’s PhD programme. The work is
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methods for integrating heterogeneous data sources—such as climate, environmental, and health surveillance data—into interpretable spatiotemporal risk models. A key methodological component could be the use
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valuation studies or care studies will be considered an advantage. Experience with qualitative document-analysis, ethnography and/or interview studies will be considered an advantage. Experience with teaching
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the closing date. Only applicants with an approved doctoral thesis and public defense are eligible for appointment. Applicants must document knowledge of a programming language for data analysis such as Python