As a senior modeling and optimization engineer, you will play a central, cross-functional role within the engineering team. Acting as the system performance conductor, you will lead multiphysics modeling of turbomachinery cycles, define optimization and Design of Experiment (DOE) strategies, and directly guide design teams on the key variables to optimize. You will join the team at a critical stage of development: full-scale prototyping of the propulsion concept. You will work closely with the CTO and all technical work-package leads.

Your main responsibilities :

• Build and maintain 0D/1D performance models of turbomachinery cycles (thermodynamics, aerodynamics, fluid mechanics), ensuring multiphysics consistency
• Lead optimization andDesign of Experiment (DOE) efforts:
  
  • Define numerical experiment plans and identify key optimization variables (efficiency, fuel consumption, emissions, weight, etc.) through sensitivity analyses and response surface methods.
    
    • Implement optimization methods (genetic algorithms, surrogate models, kriging, multi-objective optimization) to guide design decisions.
    • Propose and prioritize test campaigns based on simulation results, and calibrate models against experimental data
• Coordinate technical work-package leads (aerodynamics, thermal, structural, systems) to ensure overall consistency of models and optimization objectives
• Write technical documents: calculation notes, optimization reports, performance specifications, test requirements, and contribute to intellectual property filings (patents)

Required profile :

• Graduate of a top engineering school or holder of a Master’s/PhD in applied mathematics, energy engineering, fluid mechanics or propulsion.
• Minimum 5 years of experience in thermodynamic cycle modeling, multidisciplinary optimization or DOE in a demanding environment: aerospace, space, energy or automotive.

Required skills and qualities:

• Strong command of turbomachinery thermodynamic cycle modeling (0D/1D) and associated multiphysics couplings.
• Expertise in applied mathematics: optimization, statistics, design of experiments, surrogate modeling, sensitivity analysis.
• Proven experience in model calibration against test data and in defining experimental campaigns.
• Demonstrated ability to unite and coordinate multidisciplinary teams around system performance objectives.
• Rigor, analytical mindset and strong organizational skills
• Ability to work in a team and collaborate with diverse profiles
• Knowledge of / sensitivity to aerospace requirements and standards
• Excellent written and oral communication skills in both French and English.