One of the main research directions of our research group is diagnostics and prognostics in aviation MRO (Maintenance, Repair and Overhaul). This way, aircraft maintenance can become safer, more sustainable and cost-efficient. Under the scope of this activity, we aim at the development of data-driven predictive models for a number of aircraft components. These models are expected to be primarily categorised as Machine Learning, with enhanced provision for certifiability, trustworthiness and explainability. The main external partners for this project will be KLM Engineering & Maintenance and TU Delft. Moreover, as sharing of technical data among different parties is usually prohibited or avoided, the development of a Federated Learning architecture on which these models can be trained and executed is essential. Under this framework, the successful candidate will have to prepare the datasets and models in both centralised and decentralised versions and execute them, while comparing the model performance between the two architectures. Next to this, you will (co-)author scientific and professional publications and participate at (inter)national events.

Main activities

• Technical data extraction, preparation, exploration for a number of components (types of devices to be decided) of aircraft currently in commercial operation.
• Development of ML-based predictive health-monitoring models
• Conversion of the aforementioned models in a federated structure and implementation with the assistance of the activity partners.
• In-depth studying of the certification aspects of the developed models, with special attention to trustworthiness.
• Model validation and verification
• Dissemination of the results

As a successful applicant, you have: 

• Research background at postgraduate level in Aerospace/Mechanical/Electrical Engineering or Computer Science.
• Strong knowledge background in Data Science and Data Engineering.
• Strong programming/coding skills in Python are necessary. Other programming languages are desirable.
• Previous experience in MRO and Condition Based Maintenance (CBM) and Predictive Maintenance (PdM) is highly desirable.
• Preferably have related Federated Learning/Collaborative Learning projects experience.
• Affinity to work with and supervise students  
• Excellent team player skills: you feel at ease in a multi-stakeholder team with industry partners and researchers from other institutes.
• Proven ability for technical writing: reports, publications, papers, other forms of dissemination of research outcomes.
• Good English skills, spoken as well as written are a must. Dutch is the official language at the HvA, so it is preferable to be able to speak and write Dutch or willing to learn.

Fixed-term contract: 24 months.

Your activities will be part of the organizational function of researcher 4 and is remunerated at salary scale 10 (Collective Labor Agreement for Universities of Professional Education), with a maximum salary of €4.569,- fulltime gross per month, depending on your specific qualifications and experience. You will receive a temporary contract for 24 months.

AUAS also has an extensive package of secondary employment benefits, including an 8% vacation allowance, an end-of-year bonus of 8.3% and great sport facilities. Our AUAS Academy offers outstanding study and development opportunities, and we encourage our employees to work continuously on their professional development.

Talent as a basis, diversity as a strength

The AUAS wants to be an organization in which everyone feels welcome, appreciated and at home. As an employer, we believe that the more inclusive we are, the better we can perform as a knowledge institution of and for the city. We therefore strive to see the diversity of backgrounds and perspectives that Amsterdam has to offer reflected in the workforce of our university.

At the Aviation research group of the Faculty of Technology, we perform applied research related to real-life cases and problems in the aviation sector, with the goal of improving and innovating professional practice. We perform all our research projects in close cooperation with industry, governmental agencies and scientific institutions or universities.

More information about our Faculty of Technology is also available at www.hva.nl/faculteit/ft/over-techniek.

R&D Mobility fund research project “BrightSky”

The Aviation research group is a consortium member of the R&D Mobility Fund project "Bright Sky" in which a national partnership was formed between AUAS and other knowledge institutions, the industrial sector and national knowledge organizations. This ambitious 4-year project aims to actively contribute to smart and sustainable aviation by means of innovations in the fields of airport systems and MRO operations.

Within the Smart Availability work package, we are looking for a talented and motivated individual that will lead the activities on Predictive Maintenance on-Edge. Aircraft components deteriorate during their operation, up to the point that maintenance actions are needed. However, the physical status of such parts is usually unknown before they are removed from the aircraft, disassembled, and inspected. One of the main aircraft systems is the ECS (Environmental Control System), responsible for the preservation of the right pressure and climate conditions in the different aircraft compartments. The ECS consists of a number of components that require timely and specialised maintenance. The objective of this activity is the development of data-driven models for health monitoring, diagnostics, and prognostics, so the condition of the ECS components can be assessed before they need to be removed from the aircraft. Moreover, other main focal points are the decentralisation of data into a federated architecture and the implementation of the models on-edge, onboard the aircraft. Other partners in this work package are KLM Engineering & Maintenance and Delft  University of Technology.