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Master Thesis Student (d/f/m) on Physics-aware surrogate modelling and validation

Airbus is hiring a Master Thesis Student (d/f/m) on Physics-aware surrogate modelling and validation in Munich, Germany. Level rates it ; you can apply on Airbus.

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Job Description:

In order to support E-Aircraft Systems, Airbus Defence and Space is looking for a


Master Thesis Student on Physics-aware surrogate modelling and validation (d/f/m)

You are looking for a master thesis and want to get to know the work of a job title? Then apply now! We look forward to you supporting us in the Airbus X-Labs department as a Master student (d/f/m)!


  • Location: Taufkirchen / Ottobrunn
  • Start: 01.01.2027
  • Duration: 6 Months

Your location

Our site is just a stone's throw away from Munich, the beautiful capital of Bavaria. Are you into sports and other outdoor activities? The Alps and Lake Starnberg are within an hour’s reach, offering a multitude of recreational options.


Your benefits

  • Attractive salary and work-life balance with a 35-hour week (flexitime).
  • Traveling overseas or within Germany (team events) is possible after consultation and agreement from the department.
  • International environment with the opportunity to network globally.
  • Work with modern/diversified technologies.
  • Opportunity to participate in the Generation Airbus Community to expand your own network.

Thesis detailed description

For this thesis, you will join the design and simulation engineering team to work on advanced physics-aware surrogate modeling for megawatt-class cryogenic components, supporting next-generation electric aircraft propulsion research (such as the CryoProp demonstrator). System-level evaluations rely on 0D/1D lumped-parameter physical networks in MATLAB/Simscape; however, standard baseline models often diverge from dynamic test-bench telemetry during transient current steps and gaseous helium (GHe) coolant flow/pressure variations due to complex unmodeled physical interactions (e.g., dynamic contact resistance, thermal inertia, cryostat heat inleak).

To overcome the labor-intensive manual parameter tuning and the numerical instability (solver chattering, step-size collapse) of unconstrained black-box machine learning models, your focus will be on developing and validating a physics-aware surrogate model. Furthermore, you will deploy sparse symbolic regression to distill the learned neural dynamics into explicit, human-readable analytical equations that can be integrated back into baseline 1D Simscape model libraries.

This thesis is planned to begin in the early 2027 for an ideal duration of 6 months (start date can be adjusted). Your work will directly support the development of robust, virtual integration tools and advance model-based engineering and experimental validation strategies for future electric aircraft propulsion systems.


Your tasks and responsibilities

Depending on the exact timing and scope of the thesis, the tasks include:

  • Literature review and familiarization with Port-Hamiltonian Systems (PHS), continuous-depth Neural ODEs, symbolic regression frameworks (SINDy, PySR).
  • Analysis of experimental test-rig telemetry to identify unmodeled transient physical dynamics across varying current steps and GHe coolant conditions (T,P,m,IDC).
  • Formulation and training of an AI surrogate using the appropriately identified methods
  • Model compilation and export as an acausal model coupled natively into Simscape to be a part of a larger system model
  • Numerical validation and co-simulation benchmarking to show good performance in a system model
  • Symbolic distillation of the learned dissipation matrix into closed-form, interpretable 1D constitutive equations for physical inspection and loss breakdown.
  • Packaging a reproducible, documented modeling toolset and presenting the technical methodology and simulation results to the engineering team.

Desired skills and qualifications

You are looking for a Master Thesis in Germany, in Aerospace engineering or similar, and you have the following competences:

  • Enrolled full-time student (d/f/m) in the area of Aerospace engineering or an equivalent field of study.
  • First practical experience in the field of AI surrogate modelling.
  • First experience with handling large experimental datasets and model validation.
  • Proven competence with 0D/1D Simulation (Python, Simulink / Simscape)
  • Knowledge of industry regulatory environment is a plus
  • Comfortable working in English

Behavioural qualities essential to the exercise of the profession:

  • Have a spirit of initiative and innovation,
  • Be rigorous and reliable in your work,
  • Be autonomous and curious in your approach,
  • Be critical / self-critical,
  • Be open-minded and see beyond the limits,
  • Maintain good interpersonal skills and team spirit.
  • Be pragmatic in finding solutions, adapted to the current stage of development

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


Not a 100% match? No worries! Airbus supports your personal growth.


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

#MYCYM


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:

Final-year Thesis

-------

Experience Level:

Student

Job Family:

Support to Management <JF-FA-ES>

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.

How we rate this

Master Thesis Student (d/f/m) on Physics-aware surrogate modelling and validation at Airbus rates 21 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

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  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

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