Job Description:

In order to support the Flight Physics Capabilities department, Airbus Operations is looking for an

Intern: Large-Scale Sparse Generalized Eigenvalue Problem Solving (d/f/m)

Location: Hamburg

Start: As soon as possible

Duration: 6 months

Airbus @ Flight Physics Capabilities Hamburg

Airbus is a well known global leader in aeronautics, space and related services. The Flight Physics Capabilities team designs, develops, integrates and delivers all Flight Physics digital capabilities. It also innovates through using state of the art technologies and the application of the latest methods and tools. Within our mission we proactively support our customers inside and outside Flight Physics and bring value to the company through strengthened design processes.

You will be working at the largest production site for civil aircraft situated in Hamburg. Experience the special flair of Hamburg in your spare time where vibrant cosmopolitan culture meets nautic legacy.

Description of the Internship

In many scientific and engineering fields, particularly in structural mechanics, a critical computational step involves solving the generalized eigenvalue problem, represented by the equation: Ax=λBx

Here, A and B are large, sparse matrices, x is the eigenvector, and λ is the eigenvalue. In our software ecosystem, this calculation is fundamental for understanding the vibrational modes and frequencies of complex structures.

To enhance our computational efficiency, we are optimizing the solver for large-scale engineering problems. The standard dense matrix solver from the Eigen library, while straightforward, is not ideally suited for the performance demands of our sparse systems. An existing high-performance solution leverages the powerful PETSc framework; however, our goal is to streamline the software by reducing its complex dependency chain (SLEPc, BLAS, LAPACK, ARPACK) to improve maintainability and simplify deployment. This solution has to rely on open source libraries only (no proprietary lib authorized). This internship focuses on developing a new, efficient, and self-contained C++ solver that meets our performance requirements of a few seconds per run while minimizing external dependencies.

Your benefits

• Work-life balance with a 35-hour week (flexitime) and EUR 750 gross/monthly salary.

• A final thesis is possible after consultation with the department.

• 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.

Tasks and accountabilities

• Investigate and select a lightweight C++ library for sparse eigensolvers (like an ARPACK wrapper) based on performance, integration ease, and minimal dependencies.

• Develop a C++ solver class to solve the Ax=λBx problem, integrating the chosen library into our CMake build and handling any necessary data conversions.

• Benchmark the new solver's speed and memory usage against the baseline, and validate the numerical accuracy of the results.

• Document the solver's architecture, then prepare a final report summarizing the project's findings, design choices, and performance.

Required skills and knowledge

• Currently pursuing a degree in IT, Mathematics, Physics or engineering

• Degree requires a mandatory internship

• Good communication and interpersonal skills

• Fluent in English

• C++ programming

Please upload the following documents: cover letter, CV, relevant transcripts, enrolment certificate and valid work permit.

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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 Operations GmbH

Employment Type:

Internship

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Experience Level:

Student

Job Family:

Flight & Space Physics

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