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researcher will develop, implement, and apply advanced ways in inverting a radiative transfer model for forest trait and uncertainty mapping at satellite, airborne and drone levels. She/he will explore
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LIST? Check our website: https://www.list.lu/ How will you contribute? The Post-Doc researcher will develop, implement, and apply advanced ways in inverting a radiative transfer model for forest trait
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position within a Research Infrastructure? No Offer Description Activities: The post-doctoral fellow will be responsible for: i) Acquisition, processing, and digital classification of satellite and drone
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dynamics and behaviour, e.g. aerial/drone surveys, line transects, camera surveillance and photo-ID. Experience with Bayesian statistical modelling Proven ability to handle large ecological datasets and
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dynamics and behaviour, e.g. aerial/drone surveys, line transects, camera surveillance and photo-ID. Experience with Bayesian statistical modelling Proven ability to handle large ecological datasets and
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portable dataloggers (or analogous geophysical sensors) and continuous monitoring workflows. Background in UAS/drone mapping. Numerical modeling skills. Familiarity with coastal water-level/wave datasets and
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analysis or habitat monitoring Highly valued: Experience applying AI or machine learning methods to remote sensing data Experience with drone-based point cloud collection Experience working with or advising
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to serve teaching, research and innovation. As part of the ANR projects LEASARD and VORTEX, which aim to increase the navigation autonomy of drone fleets in complex environments via embedded AI and event
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complicated systems. These include humanoids, quadrupeds, omnidirectional drones and others. These controllers will rely on principles like Reinforcement Learning (RL), Model Predictive Control (MPC), or other
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renewable for up to two additional years (3 years total), pursuant to availability of funds. This postdoctoral scholar will work on research topics related to AI-Driven Wildfire Detection Using Drones and