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Master Thesis on Fault Detection, Isolation, and Recovery (FDIR) for AI-based Estimators (d/f/m)

Airbus

Deutschland

Vor Ort

EUR 30.000 - 50.000

Vollzeit

Vor 17 Tagen

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Zusammenfassung

An innovative opportunity awaits a master's student in a leading aerospace company, focusing on AI applications in spacecraft operations. This internship involves researching and implementing advanced Fault Detection, Isolation, and Recovery techniques, contributing to the safety and reliability of AI-driven systems. You will work in a dynamic environment, utilizing modern technologies like MATLAB/Simulink and Python, while being part of a collaborative team. Enjoy a balanced work-life with flexitime and the chance to network globally. This role promises to enhance your skills and expand your professional horizons in the exciting field of aerospace engineering.

Leistungen

Attractive salary
Work-life balance with a 35-hour week
International networking opportunities
Participation in corporate sports groups
Modern technologies

Qualifikationen

  • Full-time master's student in relevant engineering fields.
  • Experience with algorithm development in MATLAB/Simulink, Python, and C++.

Aufgaben

  • Research and analyze FDIR methodologies for AI-based systems.
  • Develop an FDIR shell for anomaly detection and fault isolation.
  • Integrate solutions in a simulation environment.

Kenntnisse

AI-based estimation
Control systems
Signal processing
Fault Detection, Isolation, and Recovery (FDIR)

Ausbildung

Master's in Aerospace Engineering
Master's in Computer Science
Master's in Electrical Engineering
Master's in Physics
Master's in Mathematics

Tools

MATLAB/Simulink
Python
C++

Jobbeschreibung

Job Description:

In order to support Airbus Defence and Space we are looking for a

Master's student

Are you looking for a master thesis opportunity and want to gain experience in spacecraft operations, Fault Detection, Isolation, and Recovery (FDIR), and AI-based estimation?

Then apply now!

We look forward to you supporting us in the department of Operations (OPS), FDIR, and Functional Verification as a Master student!
  • Location: Immenstaad
  • Start: As soon as possible
  • Duration: 6 months
About the Project

This master thesis will be carried out as part of the research activities performed within the Laboratory for Operations and On-board Autonomy Innovation, which aims to explore the application of Artificial Intelligence in space-borne systems. The specific focus of this thesis will be to investigate and implement Fault Detection, Isolation, and Recovery techniques for an AI-based attitude estimation filter. The work will contribute to enhancing the safety and reliability of AI-driven spacecraft attitude determination, particularly when traditional formal methods for Verification & Validation (V&V) are limited.

Your location

At the Airbus site in Friedrichshafen you will be working on innovation where others spend their holidays. Enjoy panoramic views of Lake Constance while having lunch in our canteen. And after work, join one of our many corporate sports groups to go running, sailing or skiing.

Your benefits
  • Attractive salary and work-life balance with a 35-hour week (flexitime).
  • International environment with the opportunity to network globally.
  • Work with modern/diversified technologies.
  • At Airbus, we see you as a valuable team member and you are not hired to brew coffee, instead you are in close contact with the interfaces and are part of our weekly team meetings.
  • Opportunity to participate in the Generation Airbus Community to expand your own network.
Your tasks and responsibilities
  • Research and analyze state-of-the-art FDIR methodologies, particularly in the context of AI-based systems.
  • Develop and implement an FDIR shell around an AI-driven attitude estimator to detect anomalies in the AI output, isolate faults and ensure system integrity and robustness.
  • Integrate and test the developed solution in a simulation environment using MATLAB/Simulink, Python, and C++.
  • Evaluate the possibility of running the algorithms on space-qualified hardware.
  • Document findings and results, with the possibility of a conference or journal publication.
Desired skills and qualifications
  • Enrolled full-time master student in Aerospace Engineering, Computer Science, Electrical Engineering, Physics, or Mathematics.
  • Background in control systems, AI-based estimation, and signal processing.
  • Experience with MATLAB/Simulink, Python, and C++ for algorithm development.
  • Understanding of fault detection and recovery methods in safety-critical systems is a plus.
  • Knowledge of VHDL coding is a plus.
  • Ability to work independently in a dynamic and research-oriented environment.
Please upload the following documents: cover letter, CV, relevant transcripts, enrollment certificate.

Take your career to a new level and apply online now!

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:
Internship

Experience Level:
Student

Job Family:
Support to Management

By submitting your CV or application you are consenting to Airbus using and storing information about you for monitoring purposes relating to your application or future employment. This information will only be used by Airbus.
Airbus is committed to achieving workforce diversity and creating an inclusive working environment. We welcome all applications irrespective of social and cultural background, age, gender, disability, sexual orientation or religious belief.

Airbus is, and always has been, committed to equal opportunities for all. As such, we will never ask for any type of monetary exchange in the frame of a recruitment process. Any impersonation of Airbus to do so should be reported to emsom@airbus.com.

At Airbus, we support you to work, connect and collaborate more easily and flexibly. Wherever possible, we foster flexible working arrangements to stimulate innovative thinking.
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