Martin Kühn

This PhD position at the Carl von Ossietzky University of Oldenburg, hosted by ForWind – Center for Wind Energy Research, focuses on the analysis and development of lidar-based minute-scale power forecasting for offshore wind farms. As the share of renewable energy in the global energy system increases, the need for accurate, continuous power forecasts becomes critical for grid stability, cost reduction, and efficient electricity trading. The research leverages scanning Doppler wind lidars to characterize wind inflow several kilometers ahead of offshore wind farms, enabling reliable forecasting of wind turbine power for up to 30 minutes and the prediction of wind ramps—sudden changes in wind speed or direction that are crucial for operational planning. The successful candidate will process large datasets by integrating lidar measurements, meteorological information, and operational wind farm data. The role involves developing, implementing, and validating forecasting algorithms, including physics-based and physics-informed machine learning approaches, for real-time applications. Additional responsibilities include analyzing uncertainty in input data and forecasts, developing methods to mitigate these uncertainties, supporting offshore measurement campaigns, and presenting scientific results at international conferences and through peer-reviewed publications. Collaboration with researchers at ForWind, Fraunhofer IWES, and other industrial and academic partners is integral to the position. The WindLab at Oldenburg offers a modern research environment with opportunities for flexible and mobile work. The university supports the PhD pathway through multidisciplinary cooperation, direct industry collaboration, a PhD network, optional secondments at international research institutes, and structured supervision. Personal, scientific, and teaching skills are developed through an individual training program and selected teaching tasks. The university fosters a family-friendly environment, offering a family service center and on-campus daycare. Funding is provided according to the TV-L E13 collective agreement for a 75% position, initially limited to three years. Benefits include secure remuneration, 30 days vacation, company pension scheme, further training opportunities, flexible working hours, health management, mobile working, and compatibility of career and family. The university is committed to increasing the percentage of female employees in science and encourages applications from women and individuals with disabilities, who will be given preference in case of equal qualification. Applicants must hold a master’s degree in Physical Science, Mechanical or Aerospace Engineering, Renewable Energy, or equivalent. Required skills include experience in handling and analyzing large datasets, statistical analysis, measurement techniques, uncertainty estimation, forecasting methods, machine learning, and Python programming. High motivation, teamwork ability, and fluency in English are essential. Wind energy research at Oldenburg is internationally recognized, with integration into ForWind and the national Wind Energy Research Alliance. The Research Laboratory for Turbulence and Wind Energy Systems brings together 50 researchers from physics, meteorology, and engineering, focusing on wind physics, turbulence modeling, and wind farm control. Facilities include wind tunnels, free-field measurement equipment, and a high-performance computing cluster. Projects often combine laboratory, field, and simulation analyses, with multi-lidar systems playing a key role. To apply, submit your application as a single PDF (motivation letter, CV, transcripts, diplomas, references) by 31.01.2026 to [email protected], referencing #AP125. Optionally, include a second PDF with your Master’s Thesis and relevant research papers. For questions, contact Prof. Dr. Martin Kühn at [email protected]. Further details about the research group and environment can be found at ForWind and Wind Energy Systems .

This postdoctoral position at the Carl von Ossietzky University of Oldenburg, within the ForWind - Center for Wind Energy Research, offers an exciting opportunity to advance the scientific application of remote sensing techniques for analysing flow physics in large offshore wind farm clusters. The research is crucial for the future of energy systems, focusing on understanding energy conversion processes under various meteorological and grid conditions to support the expansion of offshore wind energy. The position is based in the WindLab, a modern research facility, and provides a dynamic, multidisciplinary academic environment with strong links to industry and international partners. The successful candidate will develop and validate improvements in the design and operation of offshore wind farm clusters using scanning lidar, radar, and synthetic aperture radar (SAR). Key responsibilities include developing scanning strategies, analysing virtual measurements in numerical wind fields, investigating cluster wake mitigation strategies, and studying atmospheric phenomena such as coherent structures, wind ramps, low-level jets, and turbulent–nonturbulent transitions. The role also involves enhancing forecasting methods, implementing real-time forecasting algorithms, supporting offshore measurement campaigns, and processing large datasets by integrating remote sensing, meteorological, and operational wind farm data. Collaboration is central to this position, with opportunities to work closely with wind farm operators, researchers from various fields, and partner institutions such as Fraunhofer IWES and the German Aerospace Center (DLR). The research group is internationally recognised for its work in wind physics, turbulence modelling, and the control of wind turbines and wind farms. Facilities include three turbulent wind tunnels, equipment for free-field measurements, and a high-performance computing cluster, enabling comprehensive experimental and simulation-based research. The position is funded for three years, with remuneration according to the TV-L E13 collective agreement for the German public service (100% position). Additional benefits include 30 days vacation, company pension scheme, flexible working hours, health management, further training opportunities, and a family-friendly working environment with on-campus childcare. The university actively supports the career development of female scientists and candidates with disabilities. Applicants must hold a PhD in physical or engineering sciences, or a master’s degree in Physical Science, Mechanical or Aerospace Engineering, Renewable Energy, or equivalent. Required skills include experience in handling and analysing large datasets, statistical analysis, measurement techniques, uncertainty estimation, forecasting methods, machine learning, and programming in Python. High motivation, teamwork skills, and fluency in English are essential. To apply, submit your application as a single PDF file (including motivation letter, CV, transcripts, diplomas, and references) by 31 January 2026 to [email protected], referencing #AP124. Optionally, include a second PDF with your PhD thesis and relevant research papers. For further information, contact Prof. Dr. Martin Kühn at [email protected]. More details about the research group and facilities can be found at Wind Energy Systems and ForWind .