21 programming-"https:"-"https:"-"https:"-"https:"-"https:"-"UCL" positions at University of Bergen
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’ educational programme . The PhD programme comprises a training component corresponding to 30 ECTS, amounting to one semester. In total, this means that 2.5 out of four years are allocated to working
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, macroecology, remote sensing, landscape ecology, pollination, and landscape modelling, aimed at understanding the past, present and future of alpine and mountain environments worldwide. The precise research plan
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degree has been awarded. A background in algebraic topology and Topological Data Analysis is required. Experience with scientific programming or algorithm development is an advantage. Applicants must be
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years. About the PhD training: As a PhD research fellow, you will take part in the PhD programme at the Faculty of Social Sciences, UiB. The programme corresponds to a period of three years and leads
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is a requirement. Such experience may have been obtained through academic coursework, research projects, or professional employment. Experience with scientific programming using Python, R, Matlab
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. Demonstrated proficiency with scientific programming (e.g. Python) is an advantage. Demonstrated proficiency in geospatial data analysis is an advantage. Applicants must be able to work independently and in a
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training: As a PhD research fellow, you will take part in the PhD programme at the Faculty of Social Sciences, UiB. The programme corresponds to a period of three years and leads to the PhD degree. To be
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the master's degree has been awarded Solid background in mathematics and physics is a requirement Experience in scientific programming (e.g., Matlab, Python) is requirement Experience in statistical analysis
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the qualifying work including a progress plan. It is a requirement that the project is completed in the course of the period of employment. We can offer: A good and professionally stimulating working
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condition of employment that the master's degree has been awarded. Experience with Python programming, the ability to work comfortably in the Unix/Linux environment, and handling large climate datasets in