Post-Doc Researcher on broad use of AI in Aviation (ENAC Drones and UTM Chair)

Founded 70 years ago, ENAC, École Nationale de l'Aviation Civile, is Europe's largest aeronautical Grandes Écoles or university. It provides initial and advanced training for managers and key players in the civil aviation industry: engineering, air navigation, piloting, airport management, research, expertise and international development.

 
ENAC is a public scientific, cultural and professional establishment, under the supervision of the DGAC (Direction Générale de l'Aviation Civile ), the French civil aviation authority.


 
ENAC Drones and UTM Chair (Research Group), sponsored by AIRBUS and Sopra Steria, tackling the problem of safe integration of UAS into controlled and uncontrolled airspace. We strongly believe that having a complete understanding and expertise on the design, control, guidance and intelligence of UAS is the key to address these issues.
 
Currently, ENAC infrastructure includes an indoor flight arena (10mx10mx10m) with OptiTrack motion capture system, outdoor flight possibility located at Muret radio controlled model aircraft field (south of Toulouse, France), UAS expertise by the Dynamic Systems axis researchers, and the full access to the open-source autopilot system Paparazzi by the in-house developers. These capabilities lets us materialize our ideas starting from the use-cases up to the point of realistic demonstrations ! Outside !
 
Researchers working in the ENAC Drones & UTM group will also leverage ENAC's expertise on Air Traffic Management and can work with ACHIL platform which has UTM simulation capabilities.
 
If you are interested in the use of artificial intelligence in aviation, multi-agent systems, trajectory optimization, agile control, robotics and computer vision,  new guidance and mitigation methods, autonomy, learning-based solutions or basically any topics that are relevant to further progress of the UAS technology towards safe integration and operations in airspace then please consider participating our work !
 
 
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:
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.