Applied Research Scientist / Applied Research Scientistess

Job Opportunity: Autonomous Machining and Inspection Systems Developer

Our client is a leader in developing autonomous machining and inspection systems for high-precision manufacturing, catering to industries such as aerospace, MedTech, and high-end mechanical engineering. Their innovative technology integrates robotics, optics, and advanced sensing to facilitate precise, data-driven quality control of complex manufactured components.

Responsibilities

• Develop mathematical models and algorithms for high-precision optical measurement methods, translating physical and optical phenomena into robust, quantifiable models.
• Investigate how machine, sensor, and process parameters influence measurement accuracy, employing a hypothesis-driven approach that combines experimentation, data analysis, and validation.
• Quantify design trade-offs between accuracy, resolution, cycle time, and robustness, translating these insights into concrete system specifications.
• Develop and evaluate statistical inference and sensor fusion approaches in Python to quantify, model, and actively control measurement uncertainty across the system.

Profile

• A university degree (Bachelor's, Master's, or PhD) in mathematics, statistics, physics, or another comparable quantitative field.
• Strong knowledge of mathematical modeling, statistics, and numerical methods, with the ability to apply them to real-world engineering problems.
• A solid understanding of the interface between hardware and software: you know how mechanics, electronics, and optics behave in a real machine, and can translate that physical behavior into mathematical models and algorithms.
• Confident, hands-on experience using Python as a scientific working tool (e.g., NumPy, SciPy) for data analysis, modeling, and simulation.
• Strong communication skills and a genuine enjoyment of close, cross-disciplinary teamwork, with good spoken and written English or French.
• An independent, research-oriented working style, intellectual curiosity, and enthusiasm for experimental research and quantitative problem-solving.

Apply online using the form below. Please note that only applications matching the job profile will be considered.