NLR

NLR has been an ambitious applied research organisation for over 100 years, driven to make aerospace more sustainable, safer, efficient and effective through innovation. To that end, we offer specific, innovative solutions and technical expertise. We do this for instance at NLR’s state-of-the-art research infrastructure and field labs, simulators and wind tunnels. NLR works in an objective and independent manner, for and with (inter)national industry and government.

NLR contributes to a safer and more sustainable society while strengthening the competitive position of the Dutch industry. Using this approach, NLR plays a pivotal role between science, industry and government at home and abroad, bridging the gap between fundamental research and practical applications. In the field of aerospace, we are the strategic partner of the Dutch government and Defence, and whether we work for SMEs or large international companies, our commitment is the same for every project. Together with our partners, we contribute to shaping the fascinating world of tomorrow.

My name is Paul Stuiver and I have worked for two years as a Research & Development Engineer at the Netherlands Aerospace Center (NLR) within the department of Aerospace Vehicles Integrity & Life Cycle Support. Our team works on aircraft maintenance and offers specific solutions and technical expertise for industry, the Dutch government and Defence. For example, my work involves material testing to see when a material fails and performing statistical analyses that are used for structural risk analyses. In another project I look into the possibilities of AI and Machine Learning to enhance the flight data monitoring process. What I like about my work is that there is a lot of freedom to work on projects that you like. You also get the opportunity to meet experts on the field all over the world. For me, NLR provides the opportunity to apply theoretical knowledge in a practical setting.

Back in 2023 I completed my AM master's degree with a specialisation in Mathematical Systems Theory, Applied Analysis and Computational Science (SACS). Some courses that remain relevant are "Uncertainty Quantification and Data Driven Modelling", "Scientific Computing" and “Deep Learning Medical Image Analysis. Since most of my colleagues have a background in aerospace or mechanical engineering, I can contribute by applying the mathematical concepts I learnt.