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? The Faculty of Mathematics and Natural Sciences has a strategic ambition to be among Europe’s leading communities for research, education and innovation. Candidates for these fellowships will be selected in
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personalized diagnostic profile in the future. Jarli & Jordan/ UiO via Unsplash Jarli & Jordan/ UiO What skills are important in this role? The Faculty of Mathematics and Natural Sciences has a strategic
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nanotechnology. Jarli og Jordan/UiO via Unsplash Jarli og Jordan/UiO What skills are important in this role? The Faculty of Mathematics and Natural Sciences has a strategic ambition to be among Europe's leading
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Apply for this job See advertisement About the position One or two PhD Research Fellow positions are available at the Department of Mathematics in the research group of Prof. Andreas Carlson
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requirements Applicants must hold a Master’s degree (120 ECTS) or equivalent in Statistics, Computer Science, Mathematics, Computational Biology or related field, minimum grade B (ECTS grading scale
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the most relevant information of the data to make a prediction using advanced mathematical tools. This insight opens the door for enjoying the real world. The candidate further develops efficient and robust
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communities, one at Kristine Bonnevies hus at Blindern and one at Forskningsparken. dScience is affiliated with the Faculty of Mathematics and Natural Sciences at the University of Oslo. Your main tasks will be
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PhD Research Fellow in Chemistry-focus on Experiments in Chemical Kinetics and Heterogeneous Catalys
conduct catalytic experiments using advanced transient methods based on mass-spectrometry and develop mathematical models to interpret these data in terms of molecular mechanisms. International
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involve traveling within Europe, to cooperate with external organizations and visit pilot lines. Colourbox via Unsplash Colourbox What skills are important in this role? The Faculty of Mathematics and
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using advanced mathematical tools. This insight opens the door for enjoying the real world. The candidate further develops efficient and robust algorithms for realistic settings in terms of data and