Final Thesis in The Field of Data Science and Ai - Finkenwerder, Deutschland - Airbus

Airbus

Geprüftes Unternehmen

Finkenwerder, Deutschland

vor 3 Wochen

Geschrieben von:

Lena Wagner

beBee Recruiter

Beschreibung

In order to support the A320 family program chief engineering, Airbus Operations is offering a

Final thesis in the field of trend monitoring, forecasting and alerting for nonconformity handling (d/f/m)

Location:
Hamburg

Start:
From July in accordance with University planning

Duration: 6 months

Team Profile

Within the A320 family program chief engineering, you will be part of the digitalisation, data science and AI team which provides digital solutions for the chief engineering as well as the engineering support / MAP community.

Your location
You will be working at the largest production site for civil aircraft situated in Hamburg. Its location on the southern banks of the river Elbe includes the option to commute by ferry. Experience the special flair of Hamburg in your spare time where vibrant cosmopolitan culture meets nautic legacy.

Your benefits

Worklife balance with a 35hour week (flexitime).
International environment with the opportunity to network globally.
Work with modern/diversified technologies.
You will appreciate the complexity of overall aircraft nonconformity treatment
You will contribute to the introduction of new and more efficient digital ways of working.
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
We are currently investigating new AI approaches to support our chief engineering and engineering support teams on aircraft design evolution management as well as troubleshooting activities along the final assembly line process

The topic of your internship or thesis will be to develop a proof of concept for an AI based trend monitoring, forecasting and alerting strategy for time series data

In a nutshell:

Getting familiar with current tools and methods.
Review of known solutions as well as frameworks for trend monitoring, forecasting and anomaly detection
Prototyping of an AI based solution which provides trend monitoring and alerting in a trustworthy manner, i.e. compliant with EU AI act and EASA Level 1 and 2 guideline
Appropriate documentation of your work (slides, final report/thesis) in line with Airbus and university standards

Desired skills and qualifications

Currently enrolled as fulltime student (d/f/m) in the area of computer science, data science, mathematics, physics or an equivalent field of study.
Object oriented programming know how.
First practical experience with machine learning projects
Knowledge of machine learning libraries like Scikit learn, tensor flow, pytorch, hugging face as well as SQL, Python, PySpark knowledge
JavaScript knowledge would be a plus
Knowledge in agile proof of concept development (Kanban, Github, Jupyter Notebook) would be a plus
Knowledge of trend monitoring, forecasting as well as alerting would be a plus (ARIMA, RNN, LSTM, deep learning, hybrid models)
Interested to work with ontologies
Interested to work on aircraft level with multiple stakeholders, passion for aviation and a desire to learn and grow in the aerospace industry.
Ability to work independently and in a transnational team.
Fluent in English is mandatory, Fluency in German or French would be a plus

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

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

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:

Final-year Thesis
Experience Level:
Student

Job Family:

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.