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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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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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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
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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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for GIS, cartographic maps, geodata infrastructures and geo-analytical workflows; some experience with AI and machine learning methods to label texts (NLP) or data sources; strong programming skills (e.g
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or habitats knowledge of data analysis, statistical modelling or remote sensing experience with GIS, programming (R/Python) or handling large datasets demonstrated interest in method development or biodiversity
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analysis, statistical modelling or remote sensing experience with GIS, programming (R/Python) or handling large datasets demonstrated interest in method development or biodiversity research Great emphasis