The Fraunhofer IEE in Kassel conducts research in the fields of energy management and energy system technology, focusing on: energy informatics, energy meteorology and geoinformation systems, energy management and system design, energy process engineering and storage, grid planning and operation, grid stability and power conversion technology, and thermal energy technology. Around 450 scientists, employees and students develop solutions for the energy transition and generate around 40 million euros in revenue per year.
Would you like to help shape the implementation of the energy transition and work at the interface between science and industry?
As part of the EU project WinDTwin, ‘A digital twin for predicting electricity generation from wind energy’, we are looking for a motivated and detail-oriented research assistant to support the development and validation of digital twins for offshore wind farms. Your main task will be to actively contribute to the development and implementation of advanced AI and statistical models for power prediction using digital twins. We use innovative artificial intelligence methods to develop precise, dynamic and adaptive digital twins that enable highly accurate predictions of power generation and energy demand.
What you will do
* Assist in the development and validation of advanced AI and statistical models for energy forecasts in offshore wind farm digital twins.
* Utilize AI and statistical techniques to extract insights from large time series datasets.
* Collaborate within an interdisciplinary team to develop innovative algorithms for forecasting, ranging from short-term to seasonal predictions.
* Create prediction modules for digital twins and support their deployment using containerization technologies.
What you bring to the table
* Currently pursuing a master’s degree in data science, Applied Mathematics, Computer Science, Physics, Meteorology, or a related field.
* Strong interest in wind energy development and the energy transition.
* Proficient in Python or similar object-oriented programming languages.
* Experience with machine learning/statistical methods applied to time series data is advantageous.
* Familiarity with databases, containerization, and knowledge of MLOps is a plus.
* Goal-oriented with strong analytical skills, team spirit, and excellent communication in English or German.
* Independent, self-motivated, and enthusiastic about interdisciplinary collaboration.
* Interest in scientific research and the potential for a master’s thesis.
What you can expect
* Insight into application-oriented research in the energy sector with direct relevance for industry and society
* Access to expert networks in the energy industry and research
* Commitment to the Diversity Charter – we actively promote diversity and inclusion in all areas
* Optional opportunity to write a bachelor's or master's thesis on a topic of your choice
* Prospects for future permanent employment or doctoral studies
* Flexible and individual adjustment of working hours to lecture and exam times, as well as the option to work from home or in our modern institute building with a New Work concept in a central location
The monthly working hours are between 40 and 80 hours. The position is initially limited to 12 months, although we are looking to establish a longer-term working relationship. Exceptions to a shorter term are fundamental operational reasons, the personal wishes of the student or the end of their studies.
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. 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!
Questions for this job will answer you:
* Abhinav Tyagi (Tel: +49 (0) 561 7294-1664)
Fraunhofer Institute for Energy Economics and Energy System Technology IEE
Requisition Number: 81485 Application Deadline: