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- Swedish University of Agricultural Sciences
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Field
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Health, Data Science, Remote Sensing, Geomatics or a closely related discipline•Strong analytical and programming skills (e.g. Python or similar)•Experience in at least two of the following areas
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of the department and within the consortium. Where to apply Website https://emer.fa.em3.oraclecloud.com:443/hcmUI/CandidateExperience/es/job/7865/s… Requirements Research FieldBiological sciencesEducation LevelMaster
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, generating evidence to support long-term climate adaptation and investment planning. Students will build a comprehensive set of high-value technical and professional skills, including: • Geospatial and GIS
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(preferably in R, Python, GIS) • Competences in quantitative research methods - ideally knowledge of several of the following aspects of quantitative data analysis: analysis of large/longitudinal datasets
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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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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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) • 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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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
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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