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- Swedish University of Agricultural Sciences
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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) Competences in quantitative research
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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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systems (GIS). The PhD project should develop methods based on spatial indicators used to assess current and future climate risks. The IPCC's risk framework is suitable to be operationalized with spatial
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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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integration, database systems, or data quality. 2. Skills: Proficiency in Python (data processing, APIs) and good engineering practices (Git, testing, documentation). Experience with at least one: vector search
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integration, database systems, or data quality. 2. Skills: Proficiency in Python (data processing, APIs) and good engineering practices (Git, testing, documentation). Experience with at least one: vector search
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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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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
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management Nordic forestry Remote sensing data: ALS, TLS, satellite (e.g. sentinel2), aerial images Statistical modelling and analysis GIS e.g. ArcGis, Qgis, R Programming, e.g. R, Python, C etc. Field work
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methods, or forest ecology - Advanced Skills in R/Python, GIS, bioinformatics, and molecular lab work - Ability to work independently and in multidisciplinary teams - Strong English communication skills