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in Python, Julia, Matlab, R or similar languages GIS-based spatial analysis and/or geospatial data processing Knowledge of energy justice, or sustainability transitions Familiarity with renewable
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needed to be admitted to the PhD programme. Experience with data statistical analyses including knowledge of R and/or python. Experience in biodiversity- and/or ecological studies in aquatic environments
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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
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at https://www.ntnu.edu/indecol . Your immediate leader is Associate Professor Johan Berg Pettersen at Dept. of energy and process engineering and Industrial Ecology Programme. Duties of the position Conduct
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is part of the ERC-funded project “Actively learning experimental de-signs in terrestrial climate science (ACTIVATE)”: https://www.mn.uio.no/geo/english/research/projects/activate/index.html The PhD
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background and research-oriented master thesis in a related field (e.g., signal processing, statistical machine learning, applied mathematics); Significant experience with programming (preferably Python). Good
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Documented knowledge of statistical theory and methods and core machine learning methods Documented Python programming skills Desired qualifications: Experience with change point detection and anomaly
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and/or hydraulic laboratories Experience with experimental research and data analysis Analytical and programming skills for scientific computing and data analysis (e.g. Python, MATLAB, R, or similar
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(Python, C++, etc.). Experience in mathematical programming and/or optimization software such Pyomo, GAMS or similar. Proficiency in process simulation software (Aspen Plus, Aspen HYSYS, etc.). Experience
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, digital volume correlation, image registration, segmentation or quantitative image analysis. Surface metrology, profilometry or microscopy, together with statistical analysis in R, Python or equivalent