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- University of Oslo
- UiT The Arctic University of Norway
- NHH Norwegian School of Economics
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- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
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innovation. Colourbox via Unsplash Colourbox Qualification requirements Required qualifications: PhD in machine learning, statistics, computational biology, applied mathematics, physics, or similar. Eligible
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qualifications: PhD in machine learning, statistics, computational biology, applied mathematics, physics, or similar. Eligible candidates may apply before completing their PhD degree. However, a documented proof
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to the Faculty of Social Sciences’ PhD programme within relevant disciplines in the social sciences or the humanities. The master’s degree must be of high quality (grade A or B) and within a specialisation of
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, 35 doctoral and post doctoral research fellows and 13 administrative staff members. There are approximately 60 PhD. candidates and 1000 students enrolled in the Department. Apply for this job Deadline
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Competence Required qualifications A PhD degree within public economics, or other relevant fields where there is a focus on taxation, completed before starting the position. Research experience in
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(MSCA-PF) to pursue a career in research. We invite applications from promising young researchers within the field of Computational Biology & Ecological Modeling. The selected candidate will write a
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, demographic modelling, Bayesian hierarchical models and/or modelling with multiple data streams • Experience with data science and biodiversity informatics, in particular handling of scientific collection
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informatics. It is expected that all members of the centre contribute to the general activities and collaborations within RITMO. The researchers have access to state-of-the-art facilities in sound/video
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world-leading competence in musicology, psychology and informatics. It is expected that all members of the centre contribute to the general activities and collaborations within RITMO. The researchers have
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, demographic modelling, Bayesian hierarchical models and/or modelling with multiple data streams • Experience with data science and biodiversity informatics, in particular handling of scientific collection