M/F Scientist in instrumentation for AI integration into Adaptive Optics
New
- Researcher in FTC
- 18 mounth
- Doctorate
Offer at a glance
The Unit
Laboratoire d'Astrophysique de Marseille
Contract Type
Researcher in FTC
Working hHours
Full Time
Workplace
13388 MARSEILLE 13
Contract Duration
18 mounth
Date of Hire
01/06/2026
Remuneration
€3,131.32 to €4,806.76 gross/month, depending on experience.
Apply Application Deadline : 14 April 2026 23:59
Job Description
Missions
Develop and experimentally validate innovative adaptive optics approaches integrating artificial intelligence, from algorithm design to on-sky demonstration. The objective is to design intelligent adaptive optics systems capable of correcting sensor nonlinearities, anticipating atmospheric perturbations, and improving performance under realistic operational conditions.
Activity
Main activities include:
• Designing and developing deep learning models to correct wavefront sensor nonlinearities and measurement noise.
• Developing predictive control strategies based on reinforcement learning or hybrid approaches compatible with real-time adaptive optics constraints.
• Proposing and investigating innovative wavefront sensing concepts (e.g., hybrid architectures or AI-assisted sensing strategies).
• Contributing to the development and evolution of experimental adaptive optics platforms.
• Integrating and validating the developed approaches on experimental benches.
• Participating in the organization and execution of on-sky demonstrations and observational campaigns.
• Developing digital twins to accelerate the transfer from simulation to real systems.
• Analyzing system performance under realistic turbulence conditions and proposing system-level improvements.
• Disseminating results through scientific publications and presentations at international conferences.
Your Profil
Skills
Scientific and technical skills:
• PhD in applied physics, optics, astrophysics, control systems, or artificial intelligence.
• Strong background in machine learning, particularly deep learning and reinforcement learning.
• Interest in experimental instrumentation and real-world validation.
• Advanced scientific programming skills, particularly in Python (knowledge of C/C++ is a plus).
• Knowledge in adaptive optics, control systems, signal processing, or computational imaging is an advantage.
Transversal skills:
• Ability to conduct research activities independently.
• Strong analytical skills and scientific rigor.
• Ability to work at the interface between algorithm development and experimental validation.
• Capacity to collaborate effectively in a multidisciplinary environment.
• Good scientific communication skills.
Your Work Environment
The position is part of the R&D group at the Laboratoire d'Astrophysique de Marseille (LAM), a team of about 30 researchers and engineers working on advanced optical instrumentation and adaptive optics systems.
The work will benefit from:
• the laboratory's adaptive optics experimental infrastructures and test benches,
• the high-performance computing resources of CESAM, including its Machine Learning and Deep Learning hub,
• close collaborations with ONERA.
The successful candidate will work in a multidisciplinary environment bringing together researchers, engineers, PhD students, and postdoctoral fellows, at the interface between fundamental research, technological development, and experimental validation.
Compensation and benefits
Compensation
€3,131.32 to €4,806.76 gross/month, depending on experience.
Annual leave and RTT
44 jours
Remote Working practice and compensation
Pratique et indemnisation du TT
Transport
Prise en charge à 75% du coût et forfait mobilité durable jusqu’à 300€
About the offer
| Offer reference | UMR7326-ANAMEK-128 |
|---|---|
| CN Section(s) / Research Area | Astrophysics |
About the CNRS
The CNRS is a major player in fundamental research on a global scale. The CNRS is the only French organization active in all scientific fields. Its unique position as a multi-specialist allows it to bring together different disciplines to address the most important challenges of the contemporary world, in connection with the actors of change.
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