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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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skills for this position are: o Good knowledge of the technological challenges of agricultural/viticultural robotics. o Proven skills in: vision-based robot modeling and control; computer vision and
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scienceEducation LevelPhD or equivalent Skills/Qualifications PhD in computer science Background in probability, Markov chains, MDPs Knowledge about reinforcement learning and planning are a plus but not necessary
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and Climat program as well as other ongoing projects involving the supervisors, such as the OceanIA team of INRIA https://oceania.inria.cl/ . Finally, he/she will also work closely with a PhD student