Phd student (d/f/m) Intelligent Process Monitoring and Digital Twinning

• Conduct a comprehensive state-of-the-art review on 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
• Preparation of 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 - we seek candidates who go beyond standard approaches and explore novel solutions
• 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

Please upload the following documents: cover letter, CV, relevant transcripts, enrolment certificate.

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This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company’s success, reputation and sustainable growth.

Company:
Airbus Defence and Space GmbH

Employment Type:
PHD, Research
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Experience Level:
Student

Job Family:
Support to Management

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