31 algorithm-phd-"Prof" "NTNU Norwegian University of Science and Technology" PhD positions at SciLifeLab
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information about us, please visit: the Department of Biochemistry and Biophysics . About the DDLS PhD student program Data-driven life science (DDLS) uses data, computational methods and artificial
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and career advancement across the globe. DDLS industrial PhD position We are announcing the position of Data-driven life science (DDLS) PhD student in data driven cell and molecular biology. This is an
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chemistry, biochemistry and organic chemistry. More than 100 people, including around 45 PhD students, work at the department. New employees and students are recruited from all over the world and English is
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up of external funding. The staff amounts to approximately 345 employees, out of which 100 are PhD-students, and there are in total more than 700 affiliated people. Feel free to read more about the
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, computer science, computational biology and computational statistics. More information about us, please visit: Department of Mathematics . Project description We seek to recruit a PhD student for the following
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well as topics in phylogenetics. This project will involve working closely with experimentalists, and will be co-supervised by Prof Gerald McInerney and Dr Daniel Sheward, who have expertise in virology and
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The Department of Zoology at Stockholm University includes about 80 employeese, including Researchers, PhD students and administrative staff. Research and education at the department occurs in
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. General information about the PhD programs can be given by the Professor and Director of Doctoral Studies, Andreas Barth, andreas.barth@dbb.su.se . Application Apply for the PhD student position
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7 industrial PhD students. During the course of the DDLS program more than 260 PhD students and 200 postdocs will be part of the Research School. The DDLS program has four strategic research areas
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. David Marlevi, Prof. Ulf Hedin, and Dr. Ljubica Matic to improve stroke risk prediction for patients with carotid atherosclerosis using a multidisciplinary combination of data-driven imaging