Internship | Applying Knowledge Guided Machine learning Modeling Approaches for PEM Water Electrolysis

About this internship

Green hydrogen is crucial for the energy transition, providing a sustainable alternative for sectors such as steel, chemicals, and heavy industry. Proton Exchange Membrane (PEM) water electrolysis is a leading technology thanks to its high efficiency and ability to operate flexibly with renewable energy sources. As deployment accelerates, improving PEM performance and lifetime becomes increasingly important. In PEM research, experimental datasets are often limited, and electrochemical behavior is complex. To support system optimization and experimental planning, TNO develops knowledge guided modeling approaches, combining available data with established electrochemical understanding. Rather than discovering degradation mechanisms yourself, you will apply already identified mechanisms and physical insights to evaluate and develop suitable modeling approaches, which include selected ML methods that can (or cannot) incorporate domain knowledge.

What will be your role?

You will join the PEM research team at the TNO Faraday Lab in Petten, working with electrochemists, materials specialists, data scientists, AI experts and modelers.

Your tasks include:

• Data understanding and preprocessing.
• Applying known degradation insights in suitable (AI) models.
• Evaluating different modeling strategies.
• Visualizing trends and model outputs clearly.
• Explaining model behaviour in relation to known PEM mechanisms.
• Presenting intermediate and final results during team meetings.

The methodology used in this internship will be based on the following article: Chen, X., Rex, A., Woelke, J., Eckert, C., Bensmann, B., Hanke‑Rauschenbach, R., & Geyer, P. (2024). Machine learning in proton exchange membrane water electrolysis – Part I: A knowledge‑integrated framework. arXiv. arXiv:2404.03660

What we expect from you

• You are a master student (registered at a Dutch (technical) university and living in the Netherlands) in:
  • Artificial Intelligence, Data Science, Applied Physics, Chemical Engineering, Mechanical/Energy Engineering, Materials Science, or a related field.
• Experience with data analysis and numerical modeling (e.g., Python).
• Interest in combining physical knowledge with data driven methods.
• Ability to work independently and in a multidisciplinary environment.
• Good communication skills in English.

Bonus (not required):

• Basic knowledge of electrochemistry or PEM technology.
• Experience with regression modeling or simple ML methods.
• Familiarity with uncertainty or validation concepts.

What you'll get in return

• A highly professional, innovative internship environment, within a team of top experts.
• A suitable internship allowance (615 euro for wo-, hbo- and mbo-students, for a full-time internship).
• Possibility of eight hours of free leave per internship month (for a full-time internship).
• A free membership of Jong TNO, where you can meet other TNO professionals and join several activities, such as sports activities, (work-related) courses or the yearly ski-trip.
• Use of a laptop.
• An allowance for travel expenses in case you don’t receive an OV-card.

TNO as an employer

At TNO, we innovate for a healthier, safer and more sustainable life. And for a strong economy. We find each other in wonder and ingenuity. We are driven to push boundaries. There is all the space and support for your talent and ambition. You work with people who will challenge you: who inspire you and want to learn from you. Our state-of-the-art facilities are there to realize your vision. What you do at TNO matters: impact makes the difference. Because with every innovation you contribute to tomorrow’s world.