192 computer-science-intern-"https:"-"https:"-"https:"-"https:" positions at University of Oslo
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for Addiction Research Apply for this job See advertisement About the position We invite applications for a PhD Research Fellow position in Computational Structural Biology is available
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• Experience with data science and biodiversity informatics, in particular handling of scientific collection data • Solid knowledge of R, python and/or similar programming languages • Experience with
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and how to apply: https://www.jobbnorge.no/en/available-jobs/job/294601/phd-research-fellow-in-computational-medicinal-chemistry-for-cancer-drug-discovery Where to apply Website https://www.jobbnorge.no
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-computational-medicinal-chemistry-for-addiction-research Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/294598/phd-research-fellow-in-co… Requirements Research FieldPharmacological
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training activities. The PhD Fellow will take part in the approved PhD program at the Faculty of Educational Sciences and is expected to complete the project within the set fellowship period. The main
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of results through high-quality peer-reviewed publications. via Unsplash Qualifications Required A PhD in statistics, mathematics, informatics, genetics, medicine, psychology, or an equivalent field. Strong
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are motivated to explore complex questions at the intersection of health, economics, and policy. What Makes HEPARD Unique? • International and Interdisciplinary Training: Benefit from a unique opportunity to
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, University of Oslo. Are you passionate about economics, health, and public policy? Do you want to be part of a vibrant, interdisciplinary, and international research community tackling some of Europe’s most
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and maintenance of open, community resources. Centre and group information: NCMBM (https://www.med.uio.no/ncmbm/english/ ); Computational Biology & Gene Regulation group (https://mathelierlab.com
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the Section for Catalysis and Organic Chemistry at the Department of Chemistry. The group has extensive experience in computational modelling, reaction mechanisms, and machine learning for catalyst design and