Research Assistant or Fellow in Predictive Maintenance of Aircraft Systems

European Commission; United Kingdom; Hybrid; GBP 28,000 - 45,000; Full time

Job summary

Cranfield University is seeking a Research Assistant or Fellow in Predictive Maintenance of Aircraft Systems. This role involves high-quality research on AI-Enhanced Digital Twins for aircraft systems, requiring a PhD or Master's degree in relevant engineering fields. The position offers competitive salaries and the opportunity to work on industry-funded projects.

Qualifications

• PhD or Master's degree in relevant engineering field.
• Experience in aircraft systems, predictive maintenance, or digital twin technologies.
• Strong analytical and problem-solving skills.

Responsibilities

• Undertake high-quality research in AI-Enhanced Digital Twins.
• Integrate heterogeneous data streams and flag impending failures.
• Manage research tasks and coordinate project activities.

Skills

Analytical skills

Problem-solving skills

Interpersonal skills

Planning skills

Organizational skills

Education

PhD in Aerospace, Mechanical, Electrical, or Software Engineering

Master's degree (MSc) in relevant field

Tools

MATLAB

Python

Job description

Organisation/Company Cranfield University Department HR & Development Group Research Field Other Researcher Profile First Stage Researcher (R1) Recognised Researcher (R2) Positions PhD Positions Country United Kingdom Application Deadline 18 Jun 2025 - 23:59 (Europe/London) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Faculty of Engineering and Applied Sciences

Aerospace & Aviation Theme

Research Assistant or Fellow in Predictive Maintenance of Aircraft Systems

Research Assistant: Full time starting salary in the range of £28,929 to £33,825 per annum.

Research Fellow: Full time starting salary in the range of £37,337 to £44,906 per annum.

Location: Cranfield, Bedfordshire

We welcome applications from committed and skilled candidates to join our team to support and deliver to an industry funded project led by a major aircraft design company

About the Role

The purpose of this post is to support and deliver to an industry funded project led by a major aircraft design company. You will be responsible for undertaking high quality research associated with the Cranfield University project work package in AI-Enhanced Digital Twins and High-Level Reasoner Decision Support System for aircraft systems. You will integrate heterogeneous data streams (from multiple sources, such as sensory, physics model, etc.), flag impending failures, pinpoint and trace back the origin of system faults, and facilitate sensor optimization to achieve a robust and dependable condition monitoring, predictive maintenance, and prognostics and health management (PHM) regime for the aircraft systems over the entire period of their life-cycle. You will also be responsible for managing the research tasks, organising project meetings, writing project deliverables and coordinating research activities and will need excellent interpersonal

skills.

About You

You will hold a PhD in a relevant subject such as Aerospace, Mechanical, Electrical, or Software Engineering for the Research Fellow position, or hold a Master's degree (MSc, or close to completion) in one of these fields for the Research Assistant role. You will have experience in research related to aircraft systems, predictive maintenance, or digital twin technologies, using both qualitative and quantitative approaches. With strong analytical and problem-solving skills, you will be confident working independently as well as collaboratively within a multidisciplinary team.

Excellent planning, organisational, and communication skills are essential, as you will be required to coordinate research activities and engage with both academic colleagues and industry partners. A good working knowledge of programming tools like MATLAB or Python, and familiarity with aircraft systems modelling, artificial intelligence applications, and simulation tools will be highly advantageous. Your commitment to high-quality research, coupled with emotional intelligence and the ability to manage competing priorities, will help you thrive in this dynamic environment.

About Us

As a specialist postgraduate university, Cranfield’s world-class expertise, large-scale facilities and unrivalled industry partnerships are creating leaders in technology and management globally. Learn more about Cranfield and our unique impact here .

The Faculty of Engineering and Applied Science (FEAS) is a leading provider of postgraduate-level engineering education, research and technology support to individuals and organisations. At the forefront of aerospace, manufacturing and transport systems technology and management for over 70 years, we deliver multi-disciplinary solutions to the complex challenges facing the industry.

The Integrated Vehicle Health Management (IVHM) Centre is a joint effort by Industry and Academia to develop state of the art diagnostic and prognostic capabilities that change the way services are provided today. The IVHM Centre was launched by Cranfield University, Britain’s premier postgraduate, research intensive university together with Boeing, Rolls Royce, BAE Systems, Meggitt and Thales in 2008. It is located at Cranfield University’s Cranfield site. The Centre is now globally recognized, having defined the subject area and further developing new areas of expansion. The development of the Centre, along with other areas in the University, significantly contributed to the recent DARTeC (Digital Aviation Research and Technology Centre) proposal success. Through DARTeC, the IVHM Centre is leading the MRO (Maintenance, Repair and Overhaul) developments and activities with expertise and capabilities in UAV-Robotics NDT inspections, SHM–sensor monitoring, and advanced digital technologies such as Artificial Intelligence (AI) and Digital Twins (DT), tools that could be used to synchronize, monitor, and improve all processes related to Aircraft MRO.

Our intensely practical focus is supported by the people delivering our teaching and research. We work with both academics and industrialists and our team has first-hand experience in managing civil and military operations, safety regulation, accident investigation, design, and certification. This means our students get the benefit of their extensive real-world knowledge.

Our Values and Commitments

Our shared, stated values help to define who we are and underpin everything we do: Ambition; Impact; Respect; and Community. Find out more here .

We aim to create and maintain a culture in which everyone can work and study together and realise their full potential. We are a Disability Confident Employer and proud members of the Stonewall Diversity Champions Programme. We are committed to actively exploring flexible working options for each role and have beenranked in the Top 30 family friendly employers in the UK by the charity Working Families . Find out more about our key commitments to Equality, Diversity and Inclusion and Flexible Working here .

Working Arrangements

Collaborating and connecting are integral to so much of what we do. Our Working Arrangements Framework provides many staff with the opportunity to flexibly combine on-site and remote working, where job roles allow, balancing the needs of our community of staff, students, clients and partners.

How to apply

For an informal discussion about this opportunity, please contact Dr. Henrique Fernandes, Senior Lecturer in Automated Non-Destructive Testing (NDT) & Structural Health Monitoring (SHM) for Predictive Maintenance, on [e-mail] .

Closing date for receipt of applications: 18 June 2025

Please note that we reserve the right to close this advert prior to the stated closing date should we receive sufficient numbers of applications. Therefore, we would encourage you to complete and submit your application as soon as possible.