Structural Health Monitoring aims at monitoring the health of in-service structural systems for the purpose of their lifetime assessment, a topic of particular interest to expand the lifetime of wind turbines. Despite remarkable progress in structural health monitoring boosted by AI, purely data-driven models have no physical interpretability and poor generalization capabilities. Thus, they are ill-suited for inference about system's health in rapidly changing environment of wind turbines. Although physical laws can be enforced to learn a model whose parameters can be physically interpreted, there may be groups of different parameters producing the same output as the true system parameters, making it almost impossible to uniquely recover the actual ones. 

AI:Wind-Lab aims to develop a set of fundamental AI methods together with their software implementations for interpretable statistical fault prediction and lifetime assessment in the context of Structural Health Monitoring of operating wind turbines.

Two PhD stipends are available for an appointment. 

About AI:X Labs
AI:X is an ambitious initiative at Aalborg University that aims to advance AI research and create real-world impact through interdisciplinary collaboration, and nine labs will be initiated in 2026 with a total of 18 PhD stipends. 

The AI:Wind-Lab is part of the AI:X initiative with two PhD stipends and is a collaboration between the Department of Electronic Systems, the Technical Faculty of IT & Design and the Department of Mathematical Sciences, the Faculty of Engineering and Science.

The stipends are open for appointment from August 15, 2026, or soon hereafter. The duration of the position is three years.

About the applicants    

Stipend 1: The first PhD candidate should be mathematically oriented, with a strong background in control, and systems theory, skills related to modelling of mechanical systems and interest in fault diagnosis. This PhD candidate will focus on statistical lifetime assessment of a wind turbine system by combining parametric reduced order models of operating wind turbines, information contained in their differential geometry and safe data-driven control/reinforcement learning tools jointly developed with the second PhD candidate.

Stipend 2: The second PhD candidate should have a strong background in mathematics combined with interest in modern AI methods and differential geometry. The candidate will develop a safe data-driven control /reinforcement learning approach to explore the space of parameters in the context of optimising fault detection. An important part of the PhD will be devoted on controlling the probability of detections, for example using conformal prediction or other uncertainty quantification methods. 

Both PhD candidates are expected to collaborate closely with each other and with the researchers in AI:Wind-Lab. 

The PhD students will work on several tasks, including:

• development of safe data-driven control/reinforcement learning algorithms to recover parameter identifiability by exploration of different configurations of a wind turbine system,
• implementation of a control policy to favor exploration of configurations preserving accurate fault detection while enforcing physical constraints for wind turbines safety,
• proving probabilistic guarantees on the fault detection and lifetime assessment of a wind turbine,
• implementation of their solutions on actual systems.

Your competencies   

Prospective applicants should have the following qualifications:

• M.Sc. degree in either automatic control, mathematical engineering, mechanical engineering, mathematics, computer science or similar.
• Solid mathematical and analytical skills,
• Experience in programming in Python or another language, e.g., in C++, Matlab, R,
• Familiarity with basic concepts of dynamical systems,
• Knowledge of wind turbine dynamics is a plus,
• Curiosity to research and develop new solutions in collaboration with senior and junior researchers within AI:Wind-Lab.
• Readiness to collaborate with another PhD student and the researchers from other disciplines within AI:Wind-Lab.

Who we are?
The AI:Wind-Lab is composed of two researchers: Christophe Biscio and Szymon Gres, and a research mentor: Rafal Wisniewski.

Christophe Biscio is a researcher in Mathematics, with a PhD from the University of Nantes in France. He has worked 10 years at the university of Aalborg focusing on the development of statistical methodology for application in machine learning and engineering fields.

Szymon Gres is a postdoctoral researcher in Automation and Control section, whose interests are on identification and detection of stochastic dynamic systems, with a particular focus on wind energy applications. 

Rafal Wisniewski is a professor in automatic control with a background in differential geometry in mathematics and safety in control theory.

At AI:Wind-Lab we strive for an ethical and rigorous development of sciences that relies on a strong theoretical foundation without neglecting practical impact. 

Qualification requirements
PhD stipends are allocated to individuals who hold a Master's degree. PhD stipends are normally for a period of 3 years. It is a prerequisite for allocation of the stipend that the candidate will be enrolled as a PhD student at the Technical Doctoral School of IT and Design in accordance with the regulations of Ministerial Order No. 1124 of September 19, 2025 on the PhD Programme at the Universities and Certain Higher Artistic Educational Institutions. According to the Ministerial Order, the progress of the PhD student shall be assessed at regular points in time. As part of the PhD study, you are among other things required to complete PhD courses corresponding to 30 ECTS, gain experience with teaching or other forms of knowledge dissemination and complete an external research stay outside of Aalborg University, preferably 3-6 months at a foreign research institution.

How to apply
Your application must include the following:

• Application, stating reasons for applying and qualifications in relation to the position
• Curriculum Vitae (CV)
• Diplomas (bachelor's and master's degree diploma, including grades) 
• Max. 1 page summary of the topic of your MSc thesis and optionally up to 1 page self-written text on how your knowledge can be used in the project.
• Other relevant documents

The application must be submitted via Aalborg University’s recruitment system, which can be accessed under the job advertisement on Aalborg University's website. 

Aalborg University wants to reflect the surrounding society and has diversity as a core value. Therefore, everyone, regardless of personal background and orientation, is encouraged to apply for the position.

Do you have any questions?     
If you have any questions about the position, you are more than welcome to contact us. You will find contact persons at the bottom of the jobpost.

Further information  
Read more about our recruitment process here.

The assessment of candidates for the position will be carried out by qualified experts.
Shortlisting will be applied. This means that after the application deadline, the head of the department, with the assistance of the hiring committee, will select the applicants to be assessed. All applicants will be informed whether they have been shortlisted for assessment or not.

The hiring process at Aalborg University may include a risk assessment as a tool to identify potential risks associated with new hires, ensuring the safety, compliance, and integrity of the workplace.

Read more about The Technical Doctoral School of IT and Design (Stipend 1)

Read more about The Doctoral School of Engineering and Science (Stipend 2)

Salary and terms of employment
The employment is in accordance with the Ministerial Order on the Appointment of Academic Staff at Universities (the Appointment Order) and the Ministerial Order on Job Structure for Academic Staff at Universities (in Danish).

Salary and terms of employment are in accordance with the collective agreement between the Danish Confederation of Professional Associations and the state (AC collective agreement) (in Danish) 

Aalborg University - Knowledge for the world
Aalborg University is an international workplace with more than 3,700 employees. We offer real-world-oriented education and create world-class research results through collaboration between researchers, students, and public and private companies. This is how we achieve insights, new solutions to societal problems, and knowledge that changes the world. Our main campus is in Aalborg, but we also have campuses in Esbjerg and Copenhagen.