PhD in Predictive Maintenance for Aircraft Systems

A new PhD position in aerospace engineering is available at Delft University of Technology. This position is open until filled.

The faculty of Aerospace Engineering at Delft University of Technology is one of the world’s largest faculties devoted entirely to aerospace engineering. In the Netherlands it is the only research and education institute directly related to the aerospace engineering sector. It covers the whole spectrum of aerospace engineering subjects. In aeronautics, the faculty covers subjects ranging from aerodynamics and flight propulsion to structures and materials and from control and simulation to air transport and operations. In astronautics, topics include astrodynamics, space missions and space systems engineering. The faculty has around 2,700 BSc and MSc students, 225 PhD candidates and 27 professors supported by scientific staff.

The faculty’s mission is to be the best Aerospace Engineering faculty in the world, inspiring and educating students through modern education techniques and enabling staff to perform ambitious research of the highest quality for the future of aerospace. The working atmosphere at the faculty is friendly, open-minded and dedicated.

The Air Transport and Operations section is a vibrant and youthful group of 25-30 enthusiastic staff members and PhDs with 40 MSc students per year. ATO has three research aims: 1) to develop radical new ways to optimise aircraft operations for efficiency, safety, cost, and environmental impact; 2) to extend the analysis to an airline fleet and network level to include capacity and resilience; 3) to synthesise these to include operational safety at an airline and ATM level.

Modern aircraft have a large number of sensors collecting information regarding aircraft operations and system condition. Coupled with maintenance event and logistics data, aircraft and system health diagnostics and prognostics algorithms can be developed, tested and validated.

This PhD project will focus on the development, implementation and verification and validation of diagnostic and prognostic models and algorithms for aircraft systems, allowing for the adoption of a predictive approach towards aircraft maintenance and logistics. The models should extend beyond the state of the art in research, implying a strong methodological contribution. The output of these models will be employed to feed into an efficient maintenance packaging and schedule optimisation framework for adaptive aircraft fleet maintenance management. The work will be conducted as part of a large European project. Thus, the work will be fueled with real aircraft data.

The position is intended as a full-time appointment, and the work will take place at TU Delft. The researcher will have to work with several European partners and support project administration.

Applicants should have advanced analytical and modeling skills. Knowledge of and experience with stochastic modelling and machine learning techniques is a strong requirement. Experience with programming in Python or R would be a positive, as well as demonstrable experience in working with (extremely) large datasets. Applicants should preferably have knowledge of airline operations or maintenance engineering.

Very good spoken and written English is mandatory.

TU Delft offers a customisable compensation package, a discount for health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. An International Children's Centre offers childcare and an international primary school. Dual Career Services offers support to accompanying partners. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.

As a PhD candidate you will be enrolled in the TU Delft Graduate School. TU Delft Graduate School provides an inspiring research environment; an excellent team of supervisors, academic staff and a mentor; and a Doctoral Education Programme aimed at developing your transferable, discipline-related and research skills. Please visit for more information.

For more information, please contact Wim Verhagen, phone:+31 (0)15-2788190, e-mail: To apply, please e-mail a detailed CV and letter of application by 15November 2018 to V. M. van Bragt,


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