PostDoc Position / Research Assistant (f/m/d) Adaptive and Robust Control of Wind Farms Carl von Ossietzky University of Oldenburg in United Kingdom

PostDoc Position / Research Assistant (f/m/d) Adaptive and Robust Control of Wind Farms at the University of Oldenburg in Germany.

This position is focused on adaptive and robust control for wind turbines and wind farms, with an emphasis on improving grid integration, power maximisation, load reduction, noise reduction, and validation under uncertain and varying operating conditions. The successful candidate will work in the WindLab and contribute to research activities connected to ForWind, Fraunhofer IWES, and industry and academic partners.

The role includes designing control algorithms, carrying out simulation-the-loop studies using an HPC cluster, and planning and executing experimental campaigns in wind tunnel facilities or open-field experiments. Depending on background and preferences, work may be aligned with either loads-aware wind farm control for changing objectives and lifetime optimisation, or wind turbine and wind farm control in complex terrains, including uncertainty quantification, robust control, wind turbine-wind farm controller integration, and short- to mid-term power boosting.

The post is a full-time, TV-L E13 paid position and is initially limited until 31 March 2029. The University of Oldenburg offers a young research environment, flexible and mobile working, access to modern laboratory and office space, collaboration with a strong wind energy research network, optional secondment opportunities, and support for scientific and teaching development.

Eligibility highlights include a relevant master’s degree and PhD, strong control engineering knowledge, programming skills in Matlab or Python, very good English, and preferably experience in wind energy research, with German skills and international experience considered advantageous. Female candidates and applicants with disabilities are especially encouraged and supported.

Application deadline: 11 August 2026. Apply electronically with a single PDF including motivation letter, CV, one-page research statement, transcripts, degrees, and references. An additional PDF with dissertation or papers is optional. Contact Prof. Dr. Martin Kühn for questions.