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Carl von Ossietzky Universität Oldenburg
PhD Position / Research Assistant, Data scientist for wind farms, meteorology and remote sensing
Oldenburg (Oldenburg)
October 16, 2024
E13
75%
School V of Mathematics and Science, Institute of Physics, For Wind – Center for Wind Energy Research, research group »Wind Energy Systems«
Oldenburg (Old)
27.10.2024
zum nächstmöglichen Zeitpunkt
to three years
Wind energy research at the University of Oldenburg has gained international recognition by its integration into For Wind – 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 For Wind.
Job description
The main aim of your Ph D project is to further develop data processing methods for remote sensing systems, meteorological devices, and wind turbines gaining a scientific understanding and enabling new business cases for the operation of wind farms. A multidisciplinary team of wind energy experts will be available for support and guidance throughout the project.
Among others, your tasks will comprise:
- processing and analysing large amounts of data by combining lidar measurements, meteorological information, and operational wind farm data,
- developing new forecasting approaches, advanced wind field reconstruction methods and machine learning or hybrid approaches (combining physical and statistical modelling),
- deriving uncertainty quantification by virtual lidar measurements in large-eddy simulations,
- implementing and validating developed algorithms for real-time application
- cooperating closely with a wind farm operator and researchers performing high-fidelity simulations, offshore measurements and dispatch optimisation of offshore wind farm power.
We offer you the opportunity to develop your scientific career in a young and lively academic environment. You will be working in the Wind Lab – 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 Ph D is actively supported by, e.g.,
- multidisciplinary cooperation with other researchers at For Wind and Fraunhofer IWES in Oldenburg,
- direct collaboration with industry while maintaining the links with our national and international partners in academia,
- 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 Ph D process.
- a qualifying university master’s degree in physical sciences, Meteorology, Mechanical or Aerospace Engineering, Wind Energy, Wind Engineering, Remote Sensing or equivalent,
- aptitude and willingness to pursue a Ph D,
- profound knowledge of experimental or numerical fluid dynamics and statistical analysis of large data amounts,
- extensive experience in programming with at least Matlab or Python,
- high motivation and ability to jointly work on applied research topics,
- very good English skills.
- experience in handling meteorological measurement data
- knowledge of data processing in the context of wind energy systems,
- willingness to support the preparation of outdoor measurement campaigns, installation of measurement equipment, including working at high altitudes and offshore conditions.
- experience abroad of several months during school, study period or employment after graduation,
- and good German skills.
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@uol.de. Further information is available at www.forwind.de/en/ and https://uol.de/en/physics/research/we-sys.
Bitte senden Sie bis zum 27.10.2024 Ihre Bewerbung per E-Mail an
The pdf file must include either in English or German:
- A letter motivating your application.
- Curriculum vitae
- Grade transcripts and BSc/MSc diploma
- Employment references
- A one-page research statement. You are requested to present your notion of the field of the advertised Ph D topic and some initial ideas for tackling it.
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