Internship | Graduation Internship on infrastructure maintenance planning using deep reinforcement learning

Maintenance planning in large-scale infrastructure systems presents significant challenges. Traditionally, decisions on whether to repair or maintain infrastructure assets are often based purely on structural condition assessments, fixed-interval interventions and engineering judgment. This neglects the economic optimality of maintenance actions and fails to account for their impact on mobility within the network. On the other hand, typical approaches for optimal decision-making such as Markov Decision Processes perform well for small problems but scale poorly when applied to realistic infrastructure networks. Recently, Deep Reinforcement Learning (DRL) techniques have emerged as a promising solution for managing the high-dimensional state and action spaces inherent in large-scale infrastructure systems.

The aim of this thesis is to develop a method for obtaining optimal decision-making strategies for the maintenance of large infrastructure networks using DRL, and apply it on a case study focusing on Amsterdam’s historic masonry quay walls. A key innovation in this project is the integration of traffic simulations to quantify the impact of maintenance actions on urban mobility. Such effects and sub-component interaction are difficult to address with traditional heuristic maintenance approaches, which further highlights the need for a more sophisticated decision-making tool. The student can use the digital twin platform developed by TNO to perform high-performance simulations of city transit under various maintenance scenarios. This will enable the development of maintenance policies that not only account for costs and structural safety, but also minimize disruptions to the city's transportation network.

We are seeking master students from the faculties Civil Engineering and Geosciences (CEG) and Technology Policy and Management (TPM) who possess:

• Programming Skills: Proficiency in Python is essential;
• Complex systems modeling: Background knowledge in complex systems such as infrastructures;
• Optimization: Basic knowledge of optimization techniques is desirable, though not mandatory;
• Machine Learning Background: Prior experience or coursework in machine learning, particularly Reinforcement Learning (RL), is highly desirable.

You want an internship opportunity on the precursor of your career; an internship gives you an opportunity to take a good look at your prospective future employer. TNO goes a step further. It’s not just looking that interests us; you and your knowledge are essential to our innovation. That’s why we attach a great deal of value to your personal and professional development. You will, of course, be properly supervised during your work placement and be given the scope for you to get the best out of yourself. Furthermore, we provide:

• 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.

At TNO, we innovate for a healthier, safer and more sustainable life. And for a strong economy. Since 1932, we have been making knowledge and technology available for the common good. 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. Read more about TNO as an employer.

At TNO we encourage an inclusive work environment, where you can be yourself. Whatever your story and whatever unique qualities you bring to the table. It is by combining our unique strengths and perspectives that we are able to develop innovations that make a real difference in society. Want to know more? Read what steps we are taking in the area of diversity and inclusion.

After the first CV selection, the application process will be conducted by the concerning department. TNO will provide a suitable internship agreement. If you have any questions about this vacancy, you can contact the contact person mentioned below.

Important to be aware of before applying:

• Before the start of the internship, the internship agreement from TNO needs to be signed. For students at a college or university based in the Netherlands, TNO uses the UNL-template (supplemented with a number of specific agreements from TNO). For students of foreign and MBO educational institutions, the TNO internship agreement applies. TNO does not sign any other internship agreements.
• Before the start of the internship, the educational institution will need to confirm in writing that:
  • 1) you are enrolled at the educational institution during the internship, and;
  • 2) the internship takes place as part of the programme of the study.
• The confirmation of educational institution takes place by signing the UNL template or forms prepared by TNO.
• Interns at TNO must be in possession of a Dutch residential address at the start of the internship. Performance of internship activities from abroad is not possible.