Jobs

Missions include:

• Designing deep learning models to correct wavefront sensor nonlinearities and measurement noise, with direct validation on experimental benches and operational systems.
• Developing predictive control strategies (reinforcement learning and hybrid approaches) compatible with real-time AO constraints and field deployment.

• Contributing to the development and evolution of experimental AO platforms (bench architecture, calibration strategies, performance metrics).

• Proposing and testing innovative concepts in wavefront sensing (e.g., hybrid WFS architectures, AI-assisted sensing strategies).

• Leading integration, validation, and performance assessment on experimental benches and during on-sky campaigns (astronomy and free-space optical communications).

• Coordinating and conducting observational campaigns, including system configuration, calibration, and data analysis.

• Developing digital twins tightly coupled to experimental systems to accelerate sim-to-real transfer.

• Analyzing system performance under realistic turbulence and operational constraints, and proposing system-level improvements.

Profile

• PhD in applied physics, astrophysics, optics, control systems, or artificial intelligence.

• Strong background in machine learning (deep learning, reinforcement learning), ideally applied to physical systems.

• Interest in experimental instrumentation and real-world validation.

• Proficiency in Python; knowledge of C/C++ is a plus.

• Ability to lead experimental activities and interact with engineers and hardware specialists.

• Scientific rigor, autonomy, and strong analytical capacity.

Missions include:

• Contributing to the development and evolution of experimental AO platforms (real-time controller architecture, hardware interfaces, system synchronization).

• Implementing and optimizing AI-based AO algorithms (deep learning, reinforcement learning) for real-time deployment on experimental benches and operational infrastructures.

• Ensuring ultra-low latency performance compatible with high-frequency AO loops.

• Developing and maintaining interfaces between the real-time controller and hardware components (deformable mirrors, wavefront sensors, cameras, turbulence generators).

• Participating actively in integration phases, calibration procedures, and system troubleshooting.
• Supporting and participating in on-sky demonstrations and observational campaigns (astronomy and telecom links).

• Ensuring robustness, reliability, and reproducibility of experimental results.

Profile

• Engineering degree or Master’s in computer science, electronics, control systems, applied physics, or related field.
• Strong proficiency in Python and C/C++ for real-time and hardware-interfaced systems.
• Experience with GPU computing and latency optimization (CUDA, PyTorch, TensorFlow, etc.).
• Experience with experimental systems and hardware control (cameras, sensors, DM, embedded systems).
• Strong practical mindset and ability to operate complex experimental setups.
• Interest in participating in observational campaigns and field experiments.
• Rigor, autonomy, and strong teamwork skills.