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machine learning and or other mathematical approaches used in (bulk and single-cell) immune repertoire analysis is considered an advantage. Experience in statistical physics is an advantage Fluent oral and
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, with emphasis on sedimentology and petrography, and integration of complementary datasets, including seismic data. The main workload will involve field investigations, subsurface data analysis (core and
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used in (bulk and single-cell) immune repertoire analysis is considered an advantage. Experience in statistical physics is an advantage Fluent oral and written communication skills in English. Personal
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of their fellowship period within the duty component of 25 %. Place of work is Department of Informatics at Blindern, Oslo.. Project description The postdoctoral position is funded by the Department
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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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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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be placed on compatibility of the applicant’s professional and personal disposition, with strengths in: Systematic approach Analysis and assessment Implementation Self-development Initiative and
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politics, political theory, international relations and 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
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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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• 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