108 computer-science-intern-"https:"-"https:"-"https:" Fellowship research jobs at University of Oslo
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externally funded research. TIK also offers postgraduate education; a PhD-programme and two Master programmes. The Centre also hosts OSIRIS - Oslo Institute for Research on the Impact of Science. Apply
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and technology are employed in different social contexts, and with what social and political implications. The research fellow must take part in the Faculty’s approved PhD program (TIK track) and is
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inhibitors with improved efficacy The project offers a highly interdisciplinary research environment spanning computational chemistry, cell biology, physics, and materials science. The work will leverage GPU
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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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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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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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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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, informatics, genetics, medicine, psychology, or an equivalent field. Strong programming skills in Python, R, or MATLAB, with emphasis on data analysis and method development. Solid experience in statistical
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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