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(https://www.ise.fraunhofer.de/en/research-projects/pvev.html ), we are working to optimize models for PV self-consumption estimation and, on that basis, to develop an algorithm for PV feed-in upscaling
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public events. Independent work as well as collaboration with other members of the project team. Content of the research activity: Spatial analysis in GIS (e.g., in QGIS or Python) aimed at analysing
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, sustainability science, or a related field. Experience in data analysis using scripting languages such as Matlab, Python, and R. Experience working with earth observation data and visualisation of data in maps and
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-solving abilities. Strong written and oral communication skills in both English and French. Additional Skills (Preferred): Experience with environmental data analysis (R, Python, multivariate statistics
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-Doctoral Researchers: A Bachelor’s or Master's degree and a Doctoral degree from a recognized university in related fields (e.g Geographical Information Systems (GIS), Geoinformatics, or Spatial Planning
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activity: Spatial analysis in GIS (e.g., in QGIS or Python) aimed at analysing spatial relationships between data represented as vectors and rasters. WE REQUEST Professional education, qualifications and
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maintenance best practices. Experience with GIS applications (ESRI ArcGIS Online, ArcPro, etc.). Proficient with programming languages to assist with analyses (Python, R, Matlab, etc.). Salary and Benefits
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hydro-climate studies. Strong background with GIS tools and spatial analysis techniques. Demonstrated expertise in climate variability assessment and the use of climate models. Experience with
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Andres Masegosa (arma@cs.aau.dk), Department of Computer Science. (please see: https://andresmasegosa.github.io/ . The project’s domain PI is Professor Jamal Jokar Arsanjani (jja@plan.aau.dk), Department
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, geospatial analyses and/or statistical modelling, satellite data retrieval; preferably experience with Pascal programming language and R or Python and geographic information systems (GIS); a proactive attitude