Postdoctoral Researcher on Fleet Guidance by Deep Reinforcement Learning

L'ENAC, École Nationale de l'Aviation Civile, est la plus importante des Grandes Écoles ou universités aéronautiques en Europe. Elle forme à un spectre large de métiers : des ingénieurs ou des professionnels de haut niveau capables de concevoir et faire évoluer les systèmes aéronautiques et plus largement ceux du transport aérien ainsi que des pilotes de ligne, des contrôleurs aériens ou encore des techniciens aéronautiques.

Ses laboratoires de recherche sont à la pointe de l'innovation et travaillent activement en coopération avec des universités internationales de haut niveau pour un transport aérien toujours plus sûr, efficace et durable.

L'ENAC est un établissement public à caractère scientifique, culturel et professionnel – grand établissement (EPSCP-GE), sous tutelle de la DGAC (Direction Générale de l'Aviation Civile), Direction du Ministère de la Transition Écologique et Solidaire. L'ENAC comprend une direction générale localisée à Toulouse et 8 sites en France.

Pour soutenir sa dynamique en faveur de la promotion de la diversité, l'ENAC facilite l'accueil et l'intégration des travailleurs en situation de handicap.

About Us:

Our research team has been at the forefront of cutting-edge research and innovation, leveraging UAV technology to explore dynamic atmospheric phenomena and address civil security challenges. Since 2003, we have been developing and utilizing our own open-sourced autopilot system called Paparazzi, which has become a key component in our UAV research and guidance endeavors.

Our group's commitment to excellence in Atmospheric Science and UAV technology makes it an ideal environment for researchers seeking to make a meaningful impact on the world's most pressing challenges, including civil security, environmental monitoring, and anti-drone operations. We are currently seeking a highly motivated and skilled Postdoctoral Researcher to join our dynamic team and contribute to our mission of advancing UAV guidance through deep reinforcement learning in the context of 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.

Application Process:

Interested candidates are invited to submit their applications via this online recruitment portal. The application should include a cover letter, a detailed curriculum vitae, a list of publications, and the name and contact information of at least one reference. Shortlisted candidates will be contacted for further interview and discussion.