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Student / Intern with Thesis (optional) Data Science Wind Turbines
Student / Intern with Thesis (optional) Data Science Wind TurbinesFraunhofer-Gesellschaft • Hanover
Student / Intern with Thesis (optional) Data Science Wind Turbines

Student / Intern with Thesis (optional) Data Science Wind Turbines

Fraunhofer-Gesellschaft • Hanover
Vor 23 Tagen
Stellenbeschreibung

At the Fraunhofer Institute for Wind Energy Systems IWES, the energy transition becomes a reality every day. Our focus topics are : offshore wind energy, hydrogen, test infrastructure and digitization. More than 400 employees – including around 100 students – from over 50 countries work at nine locations in scientific and non-scientific teams on the development of innovative methods to accelerate the expansion of the wind energy and hydrogen economy, minimize risks, and increase cost efficiency. Do you want to join us in shaping a sustainable future?

Be part of change

You will be part of the group "Technical Reliability" at our site in Hannover. At present, our team consists of seven employees and several students. We are considering wind turbines (WT) in operation, aiming to increase the reliability of WTs and optimize operation and maintenance. To achieve this, operational and maintenance data from over 10,000 WTs are analyzed, with the functionality of the overall system always kept in focus. 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?

You will support the team by creating data-driven models for early fault detection in WTs. To do this, you will develop Normal Behavior Models (NBM), fault detection methods, and other operational analytics based on operational data from WTs. You will apply machine learning techniques and incorporate your understanding of wind energy systems, physical relationships, and heuristic connections into the interpretation and evaluation of the model results. Additionally, you will document your findings. Sounds like a lot? Do not worry, you will be supported by your colleagues in the team.

What you contribute

Are you studying Mechanical Engineering, Electrical Engineering, Energy Technology, Technical / Applied Computer Science, Data Science, or a comparable field? Do you have basic knowledge of Python, preferably with experience in modules like Pandas, Numpy, Scikit-Learn, TensorFlow, or PyTorch? Additionally, do you have a foundational understanding of physics and are familiar with physical relationships and material behavior? Have you gained initial experience with the basics of machine learning (e.g., feature engineering, model building) or have fundamental knowledge of the setup and operation of wind turbines? Do you understand and speak English? Great, then we look forward to your application.

What we offer

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.

The position is limited. Depending on the type of employment, a different contract duration may apply. In case of a student assistantship, the working time consists of up to 80 hours per month. During an internship, the working time consists of 39 hours per week. In the case of a student assistantship, remuneration is based on the general works agreement for employing assistant staff. In the case of an internship, remuneration is based on the federal government guidelines for intern salaries.

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.

Our tasks are diverse and adaptable – for applicants with disabilities, we work together to find solutions that best promote their abilities.

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.

Ready for a change? Then apply now and make a difference! Once we have received your online application, you will receive an automatic confirmation of receipt. We will then get back to you as soon as possible and let you know what happens next.

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

Requisition Number : 82597                Application Deadline :

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Student Data Science • Hanover

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