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start date: October 2026. Please quote the reference: SciEng-AY-2026-27-GI Cancer Cachexia
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all-embracing way the development of its spatial differentiation, as well as interactions between social (socioeconomic and sociocultural systems) and natural environment, also via applying GIS
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hazards and assessing their risk for the society. At the same time, they are fully qualified users of remote sensing, GIS and statistictical software techniques that can be applied to geoscience and
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spreads in natural waters. Training will cover microbial genomics, evolution assays, GIS, and advanced statistics, alongside transferable skills in interdisciplinary collaboration and science communication
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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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preferred) Experience with processing and analysing remotely sensed data Experience with GIS and spatial data analytical techniques Experience with carrying out fieldwork in related fields (e.g. Geography
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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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: Experience in method development, working with spatial data, and GIS Experience with univariate and multivariate analysis and working with large datasets Experience with working independently and organizing
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, forestry, bioinformatics, or a related field - Strong demonstrated interest in biodiversity, molecular methods, or forest ecology - Advanced Skills in R/Python, GIS, bioinformatics, and molecular lab work