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PhD, DrPH, or MD. Candidates whose programs of study emphasized public health, epidemiology, health policy & management, information science, informatics, computer science, data science, or health
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training leading to the successful completion of a PhD degree. For more information see: http://www.mn.uio.no/english/research/phd/ All candidates and projects will have to undergo a check versus national
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the Norwegian educational system The purpose of the fellowship is research training leading to the successful completion of a PhD degree. For more information see: http://www.mn.uio.no/english/research/phd
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research area or equivalent qualifications High level analytical capability Ability to communicate complex information clearly through written means (from emails to social media posts, to scientific
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to root patterning. Integrate molecular and imaging data into a spatio-temporal developmental framework. Research environment and approaches The project is highly interdisciplinary. The successful candidate
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. Proficiency in data analysis software (e.g., R, MATLAB, SPSS, Primer, Python). Experience with analytical techniques such as ANOVA, PCA, Regression, and Multidimensional Scaling (MDS). Experience in ecosystem
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epidemiological analysis of HIV epidemics in eastern and southern Africa. Postholders will be responsible for developing and leading analytical and modelling components of internationally collaborative projects
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hands-on experience in areas such as computer vision, deep learning, multi-modal sensing, robotics, structural health monitoring, or digital twin technologies. (Fresh PhD graduates are welcome
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the Norwegian educational system The purpose of the fellowship is research training leading to the successful completion of a PhD degree. For more information see: http://www.mn.uio.no/english/research/phd/ All