Master Thesis Internship: Big Data for Flight Inspection

It is a misty morning at Schiphol and you are almost back home. “This is your captain speaking” . Looking out the window you can barely see the wingtips. “Please fasten your seatbelt” . Only seconds before touchdown the airport appears from the grey haze. Taxiing to the terminal you wonder if the pilot has super-vision, or if there is something more? Flight inspection Aircraft still rely on a network of ground-based systems for localisation due to their accuracy and reliability. The localisation system used during landing is called the Instrument Landing System (ILS) , which has centimetre accuracy and allows for all-weather landings. To ensure adherence to strict regulations these systems need to be regularly inspected. Currently such flight inspection is performed by NLR using our Cessna Citation II (as can be seen on the picture above). With secondary accurate localisation equipment onboard a prescribed pattern is flown to determine the alignment, sensitivity and strength of the ILS signal. Such flights are expensive and noisy, emit CO2, reduce airport capacity, and with your help, might be unnecessary… Big data Every day thousands of aircraft arrive in the Netherlands, making use of ILS systems. These aircraft all measure the ILS signals as well as their own location, but for each individual aircraft, this data is not accurate enough for flight inspection. However, with the rise of big data, taking advantage of advances in regression methods such as gaussian process regression (GPR), one can combine the data of all these flights to improve the measurement accuracy and use this for flight inspection. This significantly reduces costs and emissions of flight inspection, and allows for increased airport capacity. What will you be doing? The goal of the internship is to develop and test a GPR-based method to use data recorded by regular aircraft to perform (part of the) flight inspection of ILS systems. The assignment consists of: Development of a GPR-based algorithm to combine uncertain measurement data. Derivation of theoretical proofs of accuracy guarantees. Preparation and execution of flight tests to validate the developed method. Writing a paper for publication of the results Duration of the internship? 9 months, starting September - November 2026. What do we offer you? A flexible, high-tech work environment and fun colleagues; A team where you get the chance to develop and learn new skills; A challenging internship; An internship allowance. Your team Our team is partially based at Rotterdam Airport, where we have a dedicated hangar for modifying and maintaining our aircraft. Each year, we conduct approximately 350 flight hours for a wide range of research and measurement flights. The other location we work at is in Amsterdam, where you will be based for your internship. The department is actively advancing in areas such as electric aviation, hydrogen-powered flight, PART 21 flight testing, and the operation of larger UAS. As the aviation industry continues to evolve, the demand for expertise in these fields is growing rapidly. Our team consists of more than 20 colleagues who work closely with the TU Delft in a multidisciplinary test flight organization. We believe that a positive working environment is essential. The atmosphere within the department is informal, collaborative, and supportive. We are committed to ensuring that everyone feels welcome and at home in our team. About NLR Royal NLR has been a knowledge organization with the will and ambition to innovate for over 100 years. Based on that motivation, we make the world of aviation and space travel safer, more sustainable, more efficient and effective and stand for groundbreaking innovations. We employ more than 1000 passionate professionals, from aircraft engineers to psychologists and from mathematicians to application experts. NLR stands for an inclusive and diverse organization where everyone feels welcome, safe, valued and respected. Want to apply? Nice! We look forward to get to know more about you. Please send you CV and cover letter via the “apply” button. Have questions, feel free to mail Pien Moller (recruiter) via [email protected] A positive VOG screening is necessary for this position.