EngD Position: LiDAR-Assisted Wind Field Forecasting for Next-Gen Turbines

About the Project

Wind energy is a cornerstone of the global energy transition, but increasing the sustainability of the turbines themselves is critical. The ECOWIND project focuses on an integrated strategy to extend operational lifespans and reduce the overall weight of wind turbines. By innovating ways to lower mechanical loads on critical components and optimizing material usage, we aim to pave the way for a truly circular wind energy sector.

Your Role
A key pillar of ECOWIND is bridging the gap between remote sensing technology and real-time turbine control. Your focus will be the development of a predictive capability that allows turbines to react to the wind before it hits the blades.

Using upstream LiDAR measurements (taken several rotor diameters ahead), you will develop a wind field forecasting method, leveraging principles like Taylor’s Frozen Turbulence Hypothesis, to estimate incoming turbulent flow. You will then assess the method’s validity under real atmospheric conditions using a combination of LiDAR data and Large Eddy Simulation (LES) results.

Key Responsibilities:

• Develop and refine numerical algorithms for real-time wind field forecasting.
• Validate forecasting models against high-fidelity LES data and field measurements.
• Quantify the impact of predictive adjustments on turbine performance and load reduction.
• Communicate findings through technical reports and presentations to both academic and industrial audiences.

Postdoctoral Researcher: High-Fidelity LES & Atmospheric Boundary Layer Modeling

About the Project

The ECOWIND project focuses on an integrated strategy to extend the operational lifespan and reduce the overall weight of wind turbines. By innovating ways to lower mechanical loads on critical components and optimizing material usage, we aim to pave the way for a truly circular wind energy sector. A key component of this mission is developing predictive "look-ahead" control capabilities based on LiDAR technology.

Your Mission: Advanced LES & Research Leadership
As a Postdoc, your primary focus will be the application and further development of open-source LES methods (e.g., OpenFOAM, SU2) to simulate a wide range of Atmospheric Boundary Layer (ABL) conditions.

Your work will provide the "ground truth" for the project. By simulating complex inflow conditions, you will create the high-fidelity datasets required to validate the Wind Field Forecasting (WFF) models developed within the team.

• LES Development & Application: Implement and extend open-source LES codes to simulate diverse ABL scenarios, including varying stability, shear, and turbulence intensities.
• Collaboration & Mentoring: Work closely with the project’s EngD researcher, providing the LES-generated data and expertise needed for the development of LiDAR-assisted forecasting methods.
• Methodological Innovation: Identify and implement improvements in LES sub-grid scale models or actuator disk/line representations to better capture turbine-atmosphere interactions.
• Scientific Impact: Lead the authoring of high-impact journal publications and present findings at major international conferences (e.g., Wind Energy Science, WESC).
• Consortium Engagement: Act as a key scientific liaison within the ECOWIND consortium, translating complex CFD results into actionable insights for structural and control engineers.

Researcher Digital Experimental Mechanics

We are looking for a Researcher to build up our experimental infrastructure and contribute to advancing mechanics education and research at UT. The role blends hands-on lab tasks, digital innovation, and joint research.

About the Role
As an Researcher in Digital Experimental Mechanics, you will contribute to modernising our experimental practice across education, research, and lab operations. You will help compose hybrid mechanics labs (hands-on + digital), develop reliable experimental workflows, support materials–surface interaction research, and contribute to long-term lab resilience. You will collaborate closely with academic staff, technicians, and researchers from Mechanical Engineering (ME), Industrial Design Engineering (IDE), and the wider Engineering Technology community. This position is ideal for someone who enjoys crafting things that work, making mechanics intuitive and accessible, and enabling others to do excellent experimental science.

What You Will Work On
You will play a key role in:

• Modernising Engineering Education
• Crafting hybrid learning experiences that combine physical experiments with simulations and datasets.
• Developing reusable, scalable teaching assets for mechanics and material-interaction courses.
• Helping students understand the link between materials, surfaces, and experienced performance.
• Building Digital & Data-Driven Workflows
• Developing standardised, traceable data acquisition and processing workflows.
• Contributing to an evolving “digital lab manual” with scripts, procedures, and guidelines.
• Improving reproducibility and efficiency in mechanical testing.
• Advancing Interaction Mechanics Research
• Supporting experimental campaigns on static and cyclic material–surface interactions.
• Collaborating on simplified digital twin models that connect experiments and simulations.
• Helping generate datasets that strengthen ongoing research lines.
• Strengthening Lab Capacity & Continuity
• Detailing critical experimental workflows and equipment procedures.
• Supporting training for staff and students.
• Contributing to a long-term continuity plan that ensures stable, future-ready laboratory operations.

Full Professor in Engineering Dynamics

At the University of Twente, you will further develop and lead research on the dynamic behaviour of structures and systems, contribute to our courses in Dynamics, and build a strong research and education team within an internationally oriented academic environment.

Job description
As a Full Professor, you will take academic leadership in Engineering Dynamics, with a focus on the theoretical description and experimental work on the dynamic behaviour of structures and systems. This in close cooperation with external partners, such as other academia, industry and governments. You have an inspiring vision on engineering themes in dynamics, highlighting the interaction of mechanical systems. Experimental validation and advanced measurement techniques, along with mathematical modelling approaches for dynamical systems are key areas of interest. You could give special attention to meso-scale applications, design challenges, interface problems, and the long-term behaviour of mechanical systems.

You will contribute to fostering a link between research and education and attract BSc and MSc students by implementation of results from research. Your vision on teaching Dynamics includes also a thorough vision on Life Long Learning initiatives, contributing to the education of the engineers of the future.

You will lead the Engineering Dynamics group ensuring its academic, financial and human resource viability and sustainability, working closely with your colleagues. You will actively acquire and carry out research projects with academic and industrial partners, supervise PhD candidates, MSc students and junior staff. You will participate in the overall management of the Department of MS3 and contribute to the research strategy of the faculty ET and to improving the educational programs Mechanical Engineering and Industrial Design Engineering of the faculty ET.

Scientific programmer of libraries on testing and learning in Haskell and Python

As a scientific programmer, you will support the development of software from a technical point of view; the researchers of the EVI project will collaborate with you and provide the research perspective. Besides pure software development (programming), you also take responsibility for ensuring quality and maintainability of the (open-source) software, for example, with respect to architectural design, and by facilitating a process including, for example, Git, testing, code reviews and usage of Docker.

Your primary task will be software development for the Haskell library Lattest for model-based testing. The library allows the user to (i) write a model of the input-output behaviours a software system is expected to have, (ii) set up the connection with a software system for executing tests consisting of inputs and outputs, and (iii) select test generation algorithms that derive tests from a given model.

As a second task, you will work on software development for model learning, and in particular, on the Python library AALpy. Model learning is done algorithmically, by sending inputs to and receiving outputs from a software system, such that a model of the actual behaviour of a software system can be constructed. In the EVI project, model learning is combined with model-based testing and model checking to construct such a model efficiently.

The EVI project is a collaboration between the University of Twente and Radboud University. As a scientific programmer you will become part of the EVI team with members from both these universities, and you will participate in joined activities. You will be based at the University of Twente, in the Formal Methods and Tools group, where the EVI members focus on the topic of model-based testing.