Phd student (d/f/m) Intelligent Process Monitoring and Digital Twinning
Clearance Level
BPSS
Salary Range
Competitive
Employment Type
FULL TIME
Work Style
onsite
// Role Summary
Airbus Defence and Space is seeking a PhD student to research intelligent process monitoring and digital twinning for cold-sprayed repair applications, aiming to enhance quality control and enable Industry 4.0 implementation.
// Key Responsibilities
- Develop a data-driven monitoring framework using ML/AI for real-time defect detection in cold spray repair.
- Create a digital twin architecture for proactive process optimization.
- Integrate sensor systems for capturing process-relevant data.
- Design and implement ML/AI models for automated pattern recognition.
- Conduct a research stay at a European partner institution if required.
- Contribute to scientific publications and industrial validation.
// Role Specification
About the Role
Airbus Defence and Space is looking for a PhD student (d/f/m) to support the Materials and Processes department. This is an excellent opportunity to conduct a PhD thesis in the field of Materials & Processes, focusing on Intelligent Process Monitoring and Digital Twinning for Cold-Sprayed Repair Applications. You will be an integral part of our team, contributing to cutting-edge research and development.
Your Tasks and Responsibilities
- Conduct a comprehensive state-of-the-art review on the detectability of process irregularities and anomalies using sensor technologies (NDT & PM).
- Identify and integrate suitable sensor systems for capturing process-relevant signals correlated with deposition parameters.
- Establish a robust data acquisition strategy and implement preprocessing pipelines for large-scale datasets (Big Data).
- Design and implement machine learning models and AI algorithms for automated recognition of process patterns and quality deviations.
- Develop a digital twin framework by linking real-time monitoring data with physical process behavior.
- Evaluate the reliability and robustness of the monitoring system under realistic conditions.
- Implement the complete data pipeline into an industrial setup for validation and demonstration.
- Prepare conference papers and scientific publications in accordance with industrial guidelines and internal approval processes.
Desired Skills and Qualifications
- Completed Master’s degree from a university in the field of Computer Science, Mechatronics, Physics, Data Science, or a related engineering or natural science discipline.
- Strong background in data signal processing and machine learning (ML/AI).
- Proven experience with programming languages such as Python, MATLAB, or C++; familiarity with ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn) is highly desirable.
- Ability to quickly grasp interdisciplinary challenges beyond your core expertise.
- Creative problem-solving skills and an innovative mindset.
- Analytical thinking and the ability to model complex physical phenomena.
- Willingness to plan, coordinate, and carry out a multi-month research stay at a European partner institution, if required.
- Basic understanding of manufacturing processes or materials science is an advantage.
- Excellent written and spoken English skills; German is a plus.
Your Benefits
- Attractive salary and work-life balance with a 35-hour week (flexitime).
- Opportunity for travel (team events) after consultation and agreement.
- International environment with the opportunity to network globally.
- Work with modern/diversified technologies.
- Be a valuable team member involved in weekly team meetings and directly connected to interfaces.
- Opportunity to participate in the Generation Airbus Community to expand your network.
Location and Duration
- Location: Manching (approx. one hour north of Munich)
- Start Date: 01.10.2026 / as soon as possible
- Duration: 36 months