Student* with Master Thesis (optional) AI-Based Blade Bearing Condition Monitoring

Hamburg, DE, 21029

Fraunhofer-Gesellschaft

Die Fraunhofer-Gesellschaft mit Sitz in Deutschland ist eine der führenden Organisationen für anwendungsorientierte Forschung. Im Innovationsprozess spielt sie eine zentrale Rolle – mit Forschungsschwerpunkten in zukunftsrelevanten...

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Who we are ...
Our primary focuses at Fraunhofer IWES are on wind energy and hydrogen technologies. Our institute is home to more than 300 scientists and employees as well as over 100 students from over 30 countries pursuing careers in applied research and development at nine sites. We secure investments in technological developments through validation, shorten innovation cycles, accelerate certification procedures, and increase planning accuracy by means of innovative measurement methods.

 

This team needs your support ...
You will be part of the group »Slewing Bearings« at our site in Hamburg. At present, our team consists of 10 employees and several students. We focus on large slewing rings. To meet the highest reliability standards for wind turbines, small and large-scale bearing test rigs are developed and operated at the Large Bearing Laboratory. Regardless of projects and backgrounds, we support each other, and open communication and collaboration are important to us. Become an active member of the team; we are keen to hear your ideas! As an international oriented IWES-team, we highly appreciate an open exchange, whether this be in German or English. Respectful cooperation is also very important to us. You are wondering what you can bring to the team?

 

What you will do

These duties await you ...
You will be involved in conducting a literature review on state-of-the-art methods for condition monitoring of blade bearings in wind turbines. Furthermore, you will focus on identifying additional suitable AI approaches for blade bearing applications and data preprocessing (feature engineering). Subsequently, you will systematically evaluate the most promising approaches identified in the literature review. Numerous datasets from previously conducted bearing tests with various types of damage will be available for this purpose. The objective is to assess the suitability of these approaches for detecting early bearing damage. You will prepare comprehensive documentation of the results.

 

What you bring to the table

What is your background?
Are you studying a technical or engineering degree such as Mechanical Engineering, Wind Energy Technology, Mechatronics, Computer Science, or a similar field? Do you have experience using Python and speak English? Do you have basic knowledge in artificial intelligence and machine learning, along with a solid mathematical and technical understanding? Great!

 

What you can expect

What we can offer you ...
We offer various opportunities to join us as a student. Whether it is an internship, where you gain a comprehensive insight into the areas of work, or the role of a student assistant, which is easy to combine with your studies. Are you looking for an exciting topic for your thesis and do you want to delve deeply into a topic scientifically? Together, we will find the right path for you! We know that studying can also be very demanding and requires a certain level of flexibility. That is no problem here, as – in agreement with your colleagues – you can decide flexibly what days and hours to work. Temporarily, you can even work remotely, depending on the job.

 

Eager to learn more?
If you would like to find out more information about the IWES, our research aspects, and your future colleagues, please visit our career website: https://s.fhg.de/5ei

 

We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability.

 

The standard contract duration is 1 year, individual agreements are possible. The working time consists of up to 80 hours per month. Remuneration according to the general works agreement for employing assistant staff.

 

With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future.

 

Interested? Apply online now. We look forward to getting to know you!

 

If you have any further questions, please contact:
People & Development
E-mail: personal@iwes.fraunhofer.de
Phone: +49 471 14 290-230

 

Only online applications via the portal can be considered.
Please note that we observe the provisions of the valid General Data Protection Regulation when processing applications.


 

Fraunhofer Institute for Wind Energy Systems 

www.iwes.fraunhofer.de 

 

Requisition Number: 78129                Application Deadline:

 

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Job stats:  2  0  0
Category: Deep Learning Jobs

Tags: Computer Science Engineering Feature engineering Machine Learning Python Research

Perks/benefits: Career development

Region: Europe
Country: Germany

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