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data (nationwide LiDAR coverage at 50 cm resolution). The candidate will perform quantitative morphometric analyses of landscapes and river networks near suspected active faults using GIS tools, Python
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Institut de Recherche pour le Développement (IRD) | Sete, Languedoc Roussillon | France | about 3 hours ago
analysis, gravity models, Bayesian models, etc.). In this regard, proficiency in software is required: programming languages such as R or Python, machine learning, econometric softwares, data management
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Information Science (GIS), and computational science for health and environment, to study processes spanning from the microscopic to the planetary, across all time scales. Subject description Forests play an important
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on research carried out within the ECUME GIS (e.g. Simon Police’s PhD thesis). To this end, working groups will be organised with GIS stakeholders and experts in maritime spatial planning, and realistic
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Twins & Energy Analytics Forecasting & Optimization Algorithms Green Hydrogen Technologies ICT Applications in Energy Systems GIS Applications in Energy Planning Interdisciplinary and innovative research
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with data analysis/modelling and programming (R or Python). Advantageous: geostatistics, digital soil mapping, remote sensing, GIS, big data or cloud tools. Proactive working style, strong communication
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languages for data handling, treatment and analysis (e.g. R, Python). • Experience in writing technical reports, scientific articles and other dissemination materials. • Excellent knowledge of English, both
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problem solving - knowledge of sensor technology and electronics, including resolving simple technical problems - experience in flying drones - experience in geographical information systems (GIS
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programming (R or Python). Advantageous: geostatistics, digital soil mapping, remote sensing, GIS, big data or cloud tools. Proactive working style, strong communication skills, and excellent English. Relevant
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multi-data analytics (e.g., health and climate/environmental data) and could include a range of data science methods, such as utilising geographical information systems (GIS), statistical analysis