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computational field and have strong Python skills. Experience with AI or NLP methods, including LLMs cloud platforms, containerisation, APIs, relational databases and data pipelines is essential. Skills in
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software (e.g. ArcGIS, QGIS) and coding environments (e.g. Python or R), collaborating across LUMHR themes, and supporting interdisciplinary research activity. Teaching support may be required, up to a
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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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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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human missions, which could extract the first Martian ice cores. You will combine GIS-based mapping and terrain analyses using data from Mars orbiters with: Numerical ice flow modelling, for example using