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-authored peer reviewed papers) • Well-developed statistical software skills (preferably in R, Python, GIS) • Competences in quantitative research methods – ideally knowledge of several of the following
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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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) • Preferably demonstrable experience in academic writing for publication (e.g. first or co-authored peer reviewed papers) • Well-developed statistical software skills (preferably in R, Python, GIS
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urban design with microclimate simulations and measurements, GIS and Digital Twin technologies, and machine learning. The work will be part of a Horizon pilot project aimed at realizing a scenario-based
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may include site visits and data collection. Experience in numerical modelling, GIS, or hydrodynamics is desirable, but not essential and training will be provided. Prior research experience and
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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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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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techniques such as thermal drones and AI modeling, with Python, R-Studio, Yolo, SLEAP, LabGym. The applicant must have proficiency in RStudio and GIS tools, as these skills are essential for data analysis and
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research papers; present research-in-progress at e.g. workshops/conferences; contribute to spatial analysis and GIS-related courses of the department; follow a 30EC training programme to prepare for your
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of the candidate Essential requirements: A 1st class or 2.1 degree (or equivalent) in Environmental Science, Remote Sensing, Computer Science, Surveying Engineering, or related field Strong coding skills (Python