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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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., examples of program codes (Python, R, SQL, GIS scripts, etc.), description or documentation of technical solutions to research problems in which the applicant participated (spatial data processing
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biochemical models, data assimilation, spatial analysis and GIS approaches. • Programing skills (e.g. R or Python) for data manipulation and visualisation, and to perform statistical analysis (e.g. mixed models
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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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with software such as R, Python, MATLAB, or SAS. 3. Climate and Environmental Science Knowledge Understanding of climate change variables (temperature, air pollution, extreme weather) and their health
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modelling, including experience in using a programming language suitable for geospatial data analysis (e.g., R, Python). Experience in applying remote sensing methods, for instance in ecological, geophysical
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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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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