Postdoc (f/m/d) - Remote sensing for analysing flow physics of offshore wind farm clusters

Internetchemie; Oldenburg; Hybrid; EUR 50.000 - 65.000; Vollzeit

Zusammenfassung

A research-focused university in Niedersachsen seeks a Postdoc for remote sensing to analyze flow physics of offshore wind farm clusters. Responsibilities include developing scanning strategies, analyzing wake mitigation techniques, and enhancing forecasting methods. The role requires a PhD in physical or engineering sciences and proficiency in programming with Python. The university offers a collaborative environment, flexible working, and support for scientific career development. Applications are due by 31.01.2026, and interested candidates should apply by email.

Leistungen

30 days vacation

Company pension scheme

Further training opportunities

Flexible working hours

Health management

Mobile working

Qualifikationen

• PhD in physical or engineering sciences is required.
• Experience analyzing large data sets and statistical analysis.
• Fluency in English communication.

Aufgaben

• Develop lidar and radar strategies for wind farm analysis.
• Analyze cluster wake mitigation strategies.
• Enhance and implement forecasting methods.

Kenntnisse

Data analysis

Programming with Python

Forecasting methods

Measurement techniques

Statistical analysis

Ausbildung

PhD degree in physical or engineering sciences

University master's degree in relevant field

Jobbeschreibung

Postdoc (f/m/d) – Remote sensing for analysing flow physics of offshore wind farm clusters

Future energy systems will rely on large offshore wind farm clusters with hundreds of turbines. An enhanced understanding of the energy conversion process at various meteorological and grid conditions is crucial for the further expansion of offshore wind. There is a growing academic and industrial interest inutilising such knowledge for improved power performance, load control, mitigation of wake losses, power forecasts and auxiliary grid services.

Your tasks

• Developing lidar and radar scanning strategies in the field and analysing virtual measurements in numerical wind fields.
• Analysing cluster wake mitigation strategies and atmospheric phenomena (e.g., coherent structures, wind ramps, low level jets, turbulent–nonturbulent transition) at different meteorological conditions.
• Enhancing forecasting methods and implementing forecasting algorithms for real-time applications.
• Supporting extensive offshore measurement campaigns.
• Processing large amounts of data by combining remote sensing measurements, meteorological information, and operational wind farm data.
• Cooperating closely with wind farm operators and researchers from different fields at universities and institutes.
• Project management, grant application and teaching tasks.

Your profile

Requirements for employment include:

• PhD degree in physical or engineering sciences.
• 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 jointly work on a complex research topic.
• Fluency in communicating and reporting in English.

Your benefits

We offer 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 – with flexible and mobile work. Your scientific qualification is actively supported by, e.g.,

• Multidisciplinary cooperation with other researchers at ForWind and Fraunhofer IWES in Oldenburg.
• Direct collaboration with industry while maintaining links with 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 network.

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 100% position.

Our standards

• The university is dedicated to increasing the percentage of female employees in science. Female candidates are strongly encouraged to apply, and female candidates with equal qualifications will be preferentially considered.
• Applicants with disabilities will be given preference in case of equal qualification.

Further benefits

• Secure remuneration according to the collective agreement
• 30 days vacation
• Company pension scheme
• Further training opportunities
• Flexible working hours
• Health management
• Mobile working
• Compatibility of career and family

Further information on the research environment

Wind energy research at the university has gained international recognition through ForWind – Center for Wind Energy Research and the Wind Energy Research Alliance of DLR, Fraunhofer IWES, and others. Our mission is to develop a deeper understanding of atmospheric and wind power plant flow physics to meet the global demand for clean, affordable electricity. We conduct laboratory experiments, free-field measurements and HPC-based simulations. Topics include wind turbulence modelling, interactions of turbulent atmospheric wind flow with wind energy systems, and control of wind turbines and wind farms. Our facilities include wind tunnels, free-field measurement equipment, and a high-performance computing cluster.

Further information is available at the university or ForWind websites. For questions regarding this job opportunity, please contact the listed administrator.

Contact

Please submit your application via email by 31.01.2026 to the listed address. Applications should be in one PDF file and include a letter motivating your application, curriculum vitae, transcripts and diplomas, and employment references. A second PDF containing your PhD thesis and relevant papers is optional.

We look forward to receiving your application.