"PhD Position / Research Assistant (f/m/d) - Analysis for lidar-based minute-scale power forecasting of Offshore Wind Farms"

PhD Position / Research Assistant (f/m/d) Analysis for lidar-based minute-scale power forecasting of Offshore Wind Farms

The increasing share of renewable energy in today's energy system drives the need for continuous power forecasts at the minute scale. Such forecasts are important for ensuring grid stability, reducing costs associated with feed-in management, and supporting electricity trading.Your tasks
We use scanning Doppler wind lidars to characterise the inflow several kilometres ahead of offshore wind farms, enabling reliable forecasting of wind turbine power for up to 30 minutes. The accurate prediction of so-called ‘wind ramps’, i.e. strong and sudden changes in wind speed or direction, is particularly crucial. To make lidar-based forecasts more practical for industrial applications, they need further development, particularly concerning the forecast horizon, measurement setup, measurement trajectories, and the prediction of wind farm effects.
Among others, your tasks will comprise:

• processing large amounts of data by combining lidar measurements, meteorological information, and operational data from wind farms,
• further developing forecasting methods and implementing and validating the developed forecasting algorithms (physics-based and physics-informed machine learning) for real-time applications.
• analysing the uncertainty of input data and forecasts and developing methods to mitigate or account for these uncertainties.
• supporting the operation of extensive offshore measurement campaigns,
• presenting scientific results at international conferences and through peer-reviewed publications to extend your specific network,
• cooperating closely with the researchers at ForWind and the other industrial and scientific partners in different research projects.

Your profile
Requirements for employment include:

• a qualifying university master’s degree in Physical Science, Mechanical or Aerospace Engineering, Renewable Energy or equivalent,
• profound knowledge and relevant experience in handling and analysing large data sets and statistical analysis,
• comprehensive skills with measurement techniques and uncertainty estimation,
• knowledge in forecasting methods and machine learning
• extensive experience in programming with Python.
• high motivation and the ability to work jointly on a complex research topic.
• fluency in communicating and reporting in English.

Your benefits
We offer you the opportunity to develop your scientific career in a young and lively academic environment. You will be working in the WindLab – one of the university's most modern office and lab spaces – while you will also have the opportunity to do flexible and mobile work. Your pathway towards the PhD is actively supported by, e.g.,

• multidisciplinary cooperation with other researchers at ForWind and Fraunhofer IWES in Oldenburg,
• direct collaboration with industry while maintaining the links with our national and international partners in academia, including a PhD network,
• optional secondment at an international research institute
• development of personal, scientific, and teaching skills through an individual training programme and selected teaching tasks,
• opportunities to present scientific results at international conferences and through peer-reviewed publications to extend your specific network,
• structured supervision of the PhD process.

Further, the university fosters a family-friendly working environment and offers a family service centre and on-campus children's daycare.The employment is initially limited to three years. The payment is based on the collective agreement for the public service in the German federal states, TV-L E13, for a 75% position.

Further information on the research environment
Wind energy research at the Carl von Ossietzky Universität Oldenburg has gained international recognition by its integration into ForWind – Center for Wind Energy Research of the Universities of Oldenburg, Hannover and Bremen and the national Wind Energy Research Alliance of the German Aerospace Center (DLR), Fraunhofer Institute for Wind Energy Systems (IWES) and ForWind.
Further information is available at www.forwind.de/en/ and https://uol.de/en/physics/research/we-sys.

For questions regarding this job opportunity, please contact Prof. Dr. Martin Kühn at +49(0)441/798-5061 or preferably by email at martin.kuehn@uni-oldenburg.de.Contact
Please submit your application via email by 31.01.2026 to
application.wesys@uni-oldenburg.dePlease submit your application electronically as one PDF file to the University of Oldenburg, Faculty V, Institute of Physics, ForWind - Center for Wind Energy Research, Research Group Wind Energy Systems, Prof. Dr. Martin Kühn, Küpkersweg 70, 26129 Oldenburg, Germany and include reference #ACA125.The PDF file must include either in English or German:

• A letter motivating your application.
• Curriculum vitae
• Grade transcripts and BSc/MSc diplomas
• Employment references

A second PDF file containing your Master’s Thesis and relevant research papers (if available) is an optional attachment.
We are looking forward to receiving your application.