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Field
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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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and describe their impacts on biodiversity and ecosystem services. To do this we use a combination of diverse methods, from empirical research to remote sensing and simulation modeling. A quantitative
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Institut National des Sciences Appliquées de Lyon | Villeurbanne, Rhone Alpes | France | 10 days ago
PhD Positions Application Deadline 1 May 2026 - 23:59 (Europe/Brussels) Country France Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Oct 2026 Is the job funded
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cutting-edge methods, models and technologies in environmental science, quaternary sciences, bedrock geology, paleontology, physical geography, biodiversity and ecosystem science, remote sensing, Geographic
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2 Apr 2026 Job Information Organisation/Company Hasselt University Research Field Engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 31 May 2026
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this framework, we are looking for a motivated PhD researcher who will work across KU Leuven and the University of Essex, at the interface of urban ecology, remote sensing, environmental epidemiology and data
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Wetsus - European centre of excellence for sustainable water technology | Netherlands | about 1 month ago
observed pipe failures, and interpreting indirect observations from remote sensing platforms such as drones and satellites. Another challenge is linking these observations to physical processes affecting
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Robotic-assisted surgery is rapidly expanding in the UK, with over 100,000 procedures performed in 2024 alone. Emerging 5G and future 6G networks are making remote surgery increasingly feasible
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large environmental and ecological data sets, incl. empirical, remote-sensing and simulated model data knowledge in programming languages (UNIX, C, or similar) and script-based programming (R, Python
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spaceborne remote sensing. You will first identify large-scale drivers of compound extremes in models and observations, then build an emulator using advanced AI methods, such as convolutional neural networks