Job Description:

In order to support the High-Lift Component Loads and Dynamics Team in Bremen, Airbus Operations is looking for a

Master student (d/f/m) for a Thesis in Uncertainty-aware Time Series Prediction with Machine Learning

You are looking for a master thesis and want to see practical applications of Machine Learning in the work of a Flight Physics Engineer? Then apply now! We look forward to you supporting us in the High-Lift Component Loads and Dynamics Team as a Master (d/f/m)!

• Location: Bremen

• Start: 01.02.2024

• Duration: 6 Months

Introduction

This thesis explores and evaluates methods for incorporating uncertainty estimates into time series predictions using machine learning models. We are looking to investigate diverse uncertainty quantification techniques, assesses their computational efficiency, and, by conducting experiments on Airbus datasets, to illustrate the effectiveness of the proposed models. The research contributes to improving the reliability and interpretability of time series forecasts, addressing a crucial aspect in practical applications for aircraft design.

Your location

Bremen is a charming city full of history in the northwest of Germany. In addition to being one of the country’s greenest cities, it offers wonderful sights, a rich culture, urban flair and culinary delights. It’s also a great place for seaside lovers, being located just an hour’s drive from the North Sea coast.

Your benefits

• Attractive salary and work-life balance with an 35-hour week (flexitime).

• Mobile working after agreement 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.

Your tasks and responsibilities

• Research methods for including uncertainty estimation within machine learning models.

• Apply these techniques to Airbus datasets

• Assess and critically evaluate the outcomes, benefits and limitations of the different approaches.

 Desired skills and qualifications

•  Enrolled full-time student (d/f/m) in the area of Aeronautical, Mechanical or Computer Science Engineering, Applied Mathematics/Mathematics or an equivalent field of study.

• First practical experience in the field of Python programming, Data Wrangling, Machine Learning is desirable. Experience in Time Series Analysis would be a bonus.

•  Fluent in German and English.

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

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

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.

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