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• Familiarity with high-throughput sequencing data and genome analysis. • Excellent written and spoken English skills, see requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html
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able to participate in the larger Cosmoglobe project (PI: Prof. Ingunn Wehus), including analysis of archival data such as AKARI and DIRBE, as well as ongoing projects (e.g., COMAP and PASIPHAE) and
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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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://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc3 • Experience with bioinformatics • Familiarity with high-throughput sequencing data and genome analysis. • Excellent written and
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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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research methods. The appointment is for a fixed, non-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
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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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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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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