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                Employer- Delft University of Technology (TU Delft)
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                Field
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                Do you want to shape the future of digital nature monitoring? Do you have experience with LiDAR, AI, and ecology — and want to contribute to remote sensing research for biodiversity and ecosystems 
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                Do you want to shape the future of digital nature monitoring? Do you have experience with LiDAR, AI, and ecology—and want to contribute to remote sensing research for biodiversity and ecosystems 
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                : You will conduct research in the field of experimental atmospheric physics, with a focus on optical remote sensing of the atmosphere up to the edge of space (mesosphere and lower thermosphere, MLT 
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                integrity and develop new ways to assess and monitor these impacts. Working at the interface of climate science, geotechnical engineering, remote sensing and critical asset management you will integrate 
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                supervised by Professor Dan Parsons, Professor Dapeng Yu (Loughborough and Previsico), Dr Quan Le (Loughborough) and Dr Chris Hackney (Newcastle). Working within the FLOOD-CDT, you’ll combine satellite remote 
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                are experience with Landsat-8 satellite data, bathymetry and other remote sensing data. Scope of responsibility: Integrate existing acoustic data collected by NOAA and CCOM/JHC, derived terrain variables and 
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                traditional forecasting with IoT offers a cost-effective, long-term solution for continuous environmental monitoring. Central to this approach is the use of self-powered sensing (SPS) nodes, which harvest 
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                , electrical engineering, computer science, physics, meteorology, or related fields. A strong interest in solar energy and the urban environment is essential, combined with solid skills in remote sensing, signal 
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                -driven simulations, optical remote sensing and biogeochemical modeling to predict seagrass distribution under various climate and nutrient scenarios. SEAGUARD aims to provide science-based recommendations 
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                amplification? 3. How effective are emerging low-cost monitoring techniques (e.g., UAV surveys, citizen science, remote sensing) in detecting and managing sediment retention? By bridging geomorphology