Postdoctoral Researcher on Fleet Guidance by Deep Reinforcement Learning

il y a 2 jours


Toulouse, France ENAC - Ecole Nationale de l'Aviation Civile Temps plein

Postdoctoral Researcher on Fleet Guidance by Deep Reinforcement Learning (FireFlies Project TSIA, ANR) ENAC - Ecole Nationale de l'Aviation Civile is seeking a highly motivated Postdoctoral Researcher to join our UAV research group focused on advancing UAV guidance through deep reinforcement learning in fleet operations. Position Overview As a Postdoctoral Researcher in our university, you will be an essential member of our UAV research group, focusing on the development and implementation of reinforcement learning algorithms for guiding fleets of UAVs in dynamic and challenging environments. Your work will center around exploring dynamic phenomena such as atmospheric phenomena (e.g., clouds) and emergency situations like fire fighting (e.g., wild fires, industrial fires). The ultimate goal is to enhance the efficiency and effectiveness of UAV fleet guidance, particularly in the context of civil security applications, while also exploring potential integration into anti-drone operations. Responsibilities Conduct cutting‑edge research in the field of reinforcement learning applied to the guidance of UAV fleets, with a specific emphasis on dynamic phenomena exploration and civil security applications. Develop and implement novel reinforcement learning algorithms, considering real‑time constraints and the unique challenges of guiding UAV fleets. Design simulation environments and conduct experiments to evaluate the performance of the reinforcement learning algorithms in various scenarios, including atmospheric conditions and emergency situations. Collaborate closely with other researchers and engineers to integrate the developed algorithms into existing UAV platforms. Stay up‑to‑date with the latest advancements in the fields of artificial intelligence, robotics, and UAV technology. Publish research findings in high‑impact journals and present at relevant conferences and workshops. Mentor and collaborate with graduate and undergraduate students in the research group. Take part in project management. Requirements Ph.D. in Computer Science, Electrical Engineering, Robotics, or a related field with a strong focus on UAVs and reinforcement learning. Proven expertise in reinforcement learning algorithms, including practical experience with popular frameworks like PyTorch. Proficiency in programming languages such as Python and C++ for algorithm development and implementation. Familiarity with Robot Operating System (ROS) and simulation platforms such as Omniverse and Isaac Sim will be highly advantageous. A track record of publications in reputable conferences and journals in the field of AI and robotics. Demonstrated ability to work independently as well as collaboratively in a team environment. Strong problem‑solving skills, analytical thinking, and mathematical aptitude. #J-18808-Ljbffr



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