PhD Position / Research Assistant (f/m/d) Data scientist for wind farms, meteorology and remote sensing

Job descriptionThe main aim of your PhD 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 applicationcooperating closely with a wind farm operator and researchers performing high-fidelity simulations, offshore measurements and dispatch optimisation of offshore wind farm power.

Job offerWe 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,optional secondment at an international research institutedevelopment 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 PhD process The employment is initially limited to three years with an intention to further prolong up to four years to facilitate a PhD.

The payment is based on the collective agreement for the public service in the German federal states, TV-L E13, for a 75 % position.

Candidate profileRequirements for employment include : 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 PhD,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.

Desired (but not mandatory) qualifications are : experience in handling meteorological measurement dataknowledge 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.BenefitsThe Carl von Ossietzky Universität Oldenburg strives to increase the proportion of women in science.

Therefore, women are strongly encouraged to apply. In accordance with 21, para. 3 NHG, female applicants will be given preferential consideration in the case of equivalent qualifications.

Severely disabled persons will be given preference in the case of equal suitability.Further, the university cares for a family-friendly working environment and offers a family service centre and children's daycare on campus.

Research environment at ForWind Carl von Ossietzky Universität OldenburgWind 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.

At ForWind, we maintain and value collaboration between our research groups and partner institutions such as the European Academy of Wind Energy members.

In Oldenburg, our 50 researchers from physics, meteorology and engineering are collaborating at the Research Laboratory for Turbulence and Wind Energy Systems centred on wind physics.

Our mission is to develop an improved understanding of atmospheric and wind power plant flow physics required to serve the global demand for clean and affordable electricity.

Therefore, we conduct laboratory experiments, free-field measurements and HPC-based numerical simulations. The main topics include the description and modelling of wind turbulence, the analysis of interactions of turbulent atmospheric wind flow and wind energy systems, as well as control of wind turbines and wind farms.

The covered scales range from small-scale turbulence up to meteorological phenomena. Our research facilities comprise three turbulent wind tunnels, various equipment for free-field measurements at on- and offshore wind farms and a high-performance computing cluster.

Almost all our projects combine analyses at more than one of these infrastructures. For instance, virtual lidar measurements can be performed in simulated three-dimensional flow fields to verify the analysis algorithms.

Our multi-lidar systems, equipped with up to three scanning lidars, are particularly important for the abovementioned research.

ContactFor questions regarding this job opportunity, please contact Prof. Dr. Martin Kühn at+49(0)441 / 798-5061 or preferably by email at martin.

[email protected]. Further information is available at www.forwind.de / en / and https : / / uol.de / en / physics / research / we-sys.

Please submit your application electronically as one PDF file by 27.10.2024 to [email protected] and include reference #ACA108.

The pdf file must include either in English or German : A letter motivating your applicationCurriculum vitaeGrade transcripts and BSc / MSc diplomaEmployment referencesA one-page research statement.

You are requested to present your notion of the field of the advertised PhD topic and some initial ideas for tackling it.

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