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- NTNU Norwegian University of Science and Technology
- NTNU - Norwegian University of Science and Technology
- University of Bergen
- UiT The Arctic University of Norway
- Norwegian University of Life Sciences (NMBU)
- Diakonhjemmet Hospital
- The Norwegian School of Sport Sciences
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Field
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of the position. Demonstrated competencies and skills within programming and statistical analyses (e.g., in Python, R, etc) are a requirement. A background in media technology & AI is a requirement, and knowledge
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imperative, both orally and written. Documented experience with scientific programming (e.g. Python, Matlab, R; any history of activity on GitHub) as well as computational or statistical methods for data
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within programming and statistical analyses (e.g., in Python, R, etc) are a requirement. A background in media technology & AI is a requirement, and knowledge in the centre’s research areas. The applicant
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selection criteria Strong skills in relevant programming languages, particularly Python and C++, good knowledge in ROS (Robot Operating System) is an advantage, and best practice in data management and use
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selection criteria Strong skills in relevant programming languages, particularly Python and C++, good knowledge in ROS (Robot Operating System) is an advantage, and best practice in data management and use
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, Atmospheric Science, Environmental Science, or related fields Good knowledge and skills in statistics and programming (e.g. R or Python) is required Experience with data analysis related to terrestrial ecology
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distribution modelling Experience with spatial analysis and mapping tools (e.g., QGIS, ArcGIS, or spatial packages in R/Python) Interest or experience in applying AI or machine learning methods to ecological
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exploring both theoretical and practical aspects of differentially private computations. Advanced programming skills, preferably experience with programming in Python. Ability to perform research in a cross
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) Documented record of advanced quantitative methods skills in R and Python, specifically Experience with GIS and spatial data analysis Experience with natural language processing or text-as-data approaches
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presentation skills in English. Solid programming skills in Python, MATLAB, or Julia and knowledge of standard optimization tools (such as CasADi or Gurobi). Strong skills in mathematics, excellent capacity