Publisher
source

Carl von Ossietzky Universität Oldenburg

PhD Position in Multi-Objective Wind Farm Control Carl von Ossietzky Universität Oldenburg in Germany

Degree Level

PhD

Field of study

Computer Science

Funding

TV-L E13, 75% position. The appointment is initially for three years with the intention to extend up to four years to facilitate the PhD. Includes secure remuneration according to the collective agreement, 30 days of vacation, company pension scheme, flexible working hours, mobile working, and other university benefits.

Deadline

Expired

Country flag

Country

Germany

University

Carl von Ossietzky Universität Oldenburg

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Keywords

Computer Science
Environmental Science
Mechanical Engineering
Electrical Engineering
Aerospace Engineering
Grid Integration
Wind Energy
Energy Engineering
Uncertainty Analysis
Power System
Physics

About this position

ForWind Oldenburg is advertising a PhD position / Research Assistant (f/m/d) in Multi-Objective Wind Farm Control at Carl von Ossietzky Universität Oldenburg, Germany. The position sits in the WESys research group and is part of the broader ForWind Center for Wind Energy Research, with close links to Fraunhofer IWES, DLR, and international partners.

This opportunity is aimed at candidates with a strong background in control engineering and related fields such as mechanical engineering, aerospace engineering, physics, wind energy, and renewable energy. The research focuses on designing wind farm control algorithms that balance power output, system services, and structural load reduction. Depending on your background and interests, you may work on either loads-aware wind farm control and lifetime optimisation or control in complex terrain, uncertainty quantification, and improved grid integration.

The role includes collaboration on high-fidelity simulation, inflow estimation, wind tunnel experiments, and field experiments at the DLR research wind farm WiValdi. The research environment is highly experimental and computational, with access to wind tunnels, free-field measurements, and HPC-based simulations. The position is designed as a structured PhD pathway with supervision, training, teaching opportunities, and an international PhD network.

Funding and conditions: TV-L E13, 75% employment. The appointment is initially for 3 years with the intention to extend to 4 years. Benefits include flexible and mobile working, 30 days of vacation, company pension scheme, family-friendly support, and access to university sports and childcare services.

Eligibility highlights: a qualifying master’s degree, strong control engineering knowledge, programming experience in Matlab or Python, very good English, and motivation for numerical and experimental research. German is not required, though it is a plus.

Deadline: 11 August 2026. Applications must be submitted electronically as a single PDF, with an optional second PDF for thesis or relevant papers.

Funding details

TV-L E13, 75% position. The appointment is initially for three years with the intention to extend up to four years to facilitate the PhD. Includes secure remuneration according to the collective agreement, 30 days of vacation, company pension scheme, flexible working hours, mobile working, and other university benefits.

What's required

A qualifying university master’s degree in Control, Mechanical or Aerospace Engineering, Physical Sciences, Wind Energy, Renewable Energy or equivalent is required. Applicants should have aptitude and willingness to pursue a PhD with numerical and experimental aspects, profound knowledge of control engineering, extensive programming experience with at least Matlab or Python, high motivation, ability to work jointly on applied research topics, and very good English skills. Desired but not mandatory: experience with wind energy topics such as wind turbine dynamics, wind turbine control, wake interaction, or wind farm control; several months abroad during school, study, or employment; and good German skills.

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Professors

Prof. Dr.

University Name
Country flag

Germany

Research Interests

Aerodynamics

Energy Engineering

Wind Engineering

Large Eddy Simulation

Lidar Technology