PhD position in wind farm fatigue load surrogating through graph-based machine learning

1 - Working at the VUB

For more than 50 years, the Vrije Universiteit Brussel has stood for freedom, equality and solidarity, and this is very much alive on our campuses among students and staff alike. 

 

At the VUB, you will find a diverse collection of personalities: innovators pur sang, but above all people who are 100% their authentic selves. With some 4,000 employees, we are the largest Dutch-speaking employer, in the private sector, in Brussels; an international city with which we are only too happy to connect and where (around) our 4 campuses are located. 

 

Add to this our principle of free research - in which self-reflection, a critical attitude and an open, creative mind around scientific and social issues are central - and you have a university that is fundamentally groundbreaking and pioneering in education and research. In short: the VUB all over again. 

 

Moreover, the VUB is a member of EUTOPIA, an alliance of like-minded European universities, all ready to reinvent themselves.

2 - Position description

The Faculty of Engineering, Department Toegepaste mechanica, is looking for a PhD-student with a doctoral grant. 

 

More concretely your work package, for the preparation of a doctorate, contains: 

We are looking for a highly motivated and skilled PhD researcher to work on graph-based machine learning surrogates of wind energy systems. Our goal is to accelerate flexible fatigue load estimation for wind turbines, with the ultimate objective of including structural health information in windfarm asset management to optimise structural lifetime consumption while guaranteeing optimal power production. 

You will work on the cutting edge of both wind energy and machine learning, two of the fastest growing scientific disciplines, to develop machine learning surrogates of wind energy systems. As newer offshore wind farms are coming online with tighter fatigue designs and more aggressive control strategies, your research will seek to assist decision-making (e.g. during operation, but also during design) to prevent over-consumption of fatigue life while balancing optimal production. This doctoral research will seek to speed up physics-based simulations of wind turbine structural responses through machine learning surrogates. In order to expand from the boundaries of the learning space, effectively generalize knowledge and extrapolate behaviour for unseen conditions, unseen locations and even unseen turbines, you will leverage the power of graph neural networks – a novel ML architecture, capable of learning fundamental physical behaviour by modeling systems as graphs and encoding nonlinearities in these. As plentiful numerical simulations and access to vast real-world monitoring data are available from the outset, your focus will be on the development and critical assessment of the surrogate models, especially their validation, how effectively they generalize and extrapolate knowledge, and how might they be improved through transfer learning. You will be supervised along your efforts by Prof. Christof Devriendt (structural integrity monitoring) and Dr. Francisco de Nolasco (graph neural networks). Additionally, you will be part of large and vibrant group of doctoral and postdoctoral researchers (∼20) involved in both fundamental and applied research on (mostly) structural health monitoring for wind energy systems. Your work will also benefit from its positioning in the European project WILLOW and the national projects Smartlife and Supersized, along with the extensive networks associated with these, but also a close contact with industrial partners and their concerns.

 

Your research will be supervised by Prof. Christof Devriendt, head of the research group on structural integrity monitoring for offshore structures and Dr. Francisco de Nolasco, postdoctoral researcher working on ML algorithms for lifetime estimation. We are part of the Acoustics & Vibration Research Group itself part of the Department of Mechanical Engineering, Faculty of Engineering of the Vrije Universiteit Brussel (VUB). Our research group is a founding member of the Offshore Wind Infrastructure Application Lab (OWI-Lab) and, as part of it and our projects, you’ll be embedded in an international research setting, with access and the possibility to collaborate with experts all around the world. 

This research fits within the European project WILLOW, focused on developing data-driven smart (fatigue-aware) curtailment tools and the national funded project Smartlife, leveraging model and data-driven digital twins for smart asset management and lifetime optimization of offshore windfarms. 

 

For this function, our Brussels Humanities, Sciences & Engineering Campus (Elsene) will serve as your home base. 

3 - Profile

What do we expect from you?

 

• Master's degree in a relevant field (e.g., mechanical and/or electrical engineering, civil engineering, energy, or computer science)

 

• Holds at least a Master's degree in a relevant field (e.g., mechanical/electrical engineering, civil engineering, energy, computer science).
• Strong motivation to conduct high-level scientific research.
• Good analytical and technical skills.
• Interest in the mechanical behavior of structural components, monitoring techniques, and offshore wind energy.
• Experience with data analysis, machine learning, and programming in Python is an advantage.
• Knowledge of graph neural networks (GNNs) and their application to complex systems is highly regarded.
• Capable of working independently, solving problems creatively, and managing your project in a well-structured manner.
• Open personality with a collaborative attitude and willingness to contribute to team efforts and didactic projects.
• Excellent communication skills in English, both written and oral.

 

• You have not performed any works in the execution of a mandate as an assistant, paid from operating resources, over a total (cumulated) period of more than 12 months.

 

The VUB wants to be a reflection of the society where everyone's talent is valued, regardless of gender, age, religion, skin color, migration background, disability and neurodiversity.

4 - Offer

Are you going to be our new colleague?

 

You’ll be offered a full-time PhD-scholarship, for 12 months (extendable up to max. 48 months, on condition of the positive evaluation of the PhD activities), with planned starting date 01/02/2025. 

 

You’ll receive a grant linked to one of the scales set by the government.

 

IMPORTANT: The effective result of the doctorate scholarship is subject to the condition precedent of your enrolment as a doctorate student at the university.

 

At the VUB, you’re guaranteed an open, involved and diverse workplace where you are offered opportunities to (further) build on your career.

 

As well as this, you will also enjoy various other benefits:

• Extensive homeworking options, a telework allowance of 50 euros per month OR an internet fee of 20 euros per month;
• An open and informal working environment where attention is paid to work-life balance, and exceptional holiday arrangements with 35 days of leave (based on a fulltime contract), closure between Christmas and New Year and 3 extra leave days;
• Cost-free hospitalisation insurance;
• Full reimbursement of your home-to-work commute with public transport according to VUB-policy, and/or compensation if you come by bike; 
• A wide selection of meals in our campus restaurants at attractive prices;
• Excellent and affordable facilities for sport and exercise, a range of discounts via Benefits@Work (in  all kinds of shops, on flights, in petrol stations, amusement parks...) and Ecocheques; 
• Nursery near campus, discount on holiday camps; 
• The space to form your job content and to continuously learn through our VUB learning platforms and training courses;
• And finally: great colleagues with a healthy drive.

5 - Interested?

Is this the job you’ve been dreaming of?

 

Then apply, at the latest on 15/01/2025, via jobs.vub.be, and upload the following documents:

• your CV;
• your motivation letter;
• your diploma (not applicable for VUB alumni).

 

Do you have questions about the job content? Contact Francisco de Nolasco Santos at francisco.de.nolasco.santos@vub.be or on +351 916236151.

 

Would you like to know what it’s like to work at the VUB? Go to jobs.vub.be, and find all there is to know about our campuses, benefits, strategic goals and your future colleagues.

 

Would you like more information about EUTOPIA? Go to eutopia-university.eu, and read more about the role of the VUB in the development of the EUTOPIA alliance.