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Field
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Strong programming skills, particularly in Python Familiarity with knowledge graphs Experience with graph neural network Personal Qualities We value candidates who are: Intellectually curious Self
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, mathematics, or related scientific disciplines. Skills in numerical tools and programming are desirable (MATLAB, python, C++ etc). Any experience or capabilities in engineering design or manufacturing methods
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and geoprocessing of environmental data; Competences in quantitative data analysis and statistical modelling applied to ecological studies; Experience in the use of programming languages such as Python
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. Experience in one or more scientific computing languages (Julia, Python, Matlab, etc) You must meet the requirements for admission to the faculty's Doctoral Programme (https://www.ntnu.edu/nv/phd) Good oral
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, Computer Science, Neuroscience, Data Science, or a related field. An MSc degree in a relevant area is desirable though not necessary. Experience in coding (e.g., Python/R/Matlab) and experience in
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economics, market design, and policy-relevant research. Experience with numerical, computational, or simulation-based methods (e.g. Matlab, Python, R, or similar); experience with statistical software is an
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well as European coastal and marine policies (especially EU-MSFD, EU-WFD and EU Nature Restoration Law) Experience in numerical model data extraction with Python and data analysis in R as well as experience in
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++, or python; - very good communication skills (French or English), both oral and written; - a strong motivation for research and a taste for analytical and theoretical subjects. LanguagesENGLISHLevelExcellent
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Experience with R, Python, image analysis, or genetic data analysis (GWAS) is an advantage Motivation to work in interdisciplinary and international research environments You need to: Be able to work
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, deposition and transport behaviour. • Wastewater treatment modelling, including aeration energy, sludge production, nutrient removal and AD performance. • MATLAB/Python-based data analysis, multi-source data