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funding calls. REQUIRED PROFILE • PhD in Hydrology, Environmental Science, Remote Sensing, Data Science, Civil Engineering, or a related field. • Strong background in hydrological modelling, time
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project deliverables are met. Any other ad-hoc duties assigned by Supervisor. Job Requirements PhD in Geography, GIS, Remote Sensing, Environmental Science, Earth Science, or related disciplines. Strong
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that does not reflect local reality and thereby create unfair comparisons. Your work will include measurements of greenhouse gases (CO2, CH4, N2O) using drones and various sensors, as well as remote sensing
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YOUNG RESEARCHER IN THE FIELD OF EARLY DETECTION OF THE HEALTH STATUS OF PLANTS USING REMOTE SENSING
Mathematics » Statistics Geosciences » Other Technology » Remote sensing Engineering » Agricultural engineering Computer science » Programming Computer science » Informatics Computer science » 3 D modelling
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consider one or multiple subtopics that our group is particular interested in and invests on: (1) ice microphysics remote sensing from infrared to microwave spectra (TIR, FIR, sub-mm, MW); (2) cloud
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, especially in the remote and ice-covered Arctic Ocean. We have an opening for a 3-year PhD fellow position, connected to our Data Assimilation group, conducted in collaboration with our Sea Ice and Ocean
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DC-26094– POSTDOC/DATA SCIENTIST – AI-DRIVEN CLIMATE RISK MODELLING AND EARLY WARNING SYSTEMS FOR...
: https://www.list.lu/ How will you contribute? You will be part of LIST’s Remote sensing and natural resources modelling group Embedded in the Environmental Sensing and Modelling (ENVISION) unit
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sediment monitoring framework combining in situ observations and satellite remote sensing. The project directly supports EU policies including the Common Agricultural Policy, Soil Monitoring Law and Nitrates
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bring strong research expertise and strong technical skills within remote sensing and ecology, notably lidar processing. The successful candidate should have: Required: A PhD degree with a publication
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decades, the rapidly expanding volume of satellite and other remote sensing data has greatly assisted the fault trace mapping. The mapping is commonly done manually: the expert recognizes the fracture and