Fixed Term Contract for 2 years
Flexible working will be actively considered
Starting salary: £33,809 per annum
Location: Cranfield, Bedfordshire
Cranfield University’s world-class expertise, large-scale facilities and unrivalled industry partnerships is creating leaders in technology and management globally. Learn more about Cranfield and our unique impact here.
Cranfield University School of Aerospace, Transport and Manufacturing welcomes applications from motivated and talented post doctoral researchers with experience of investigating driver behaviour and working with large data sets. You will be joining an exciting, vibrant team involved in cutting edge research and teaching provision.
About the School of Aerospace, Transport and Manufacturing
The School of Aerospace, Transport and Manufacturing (SATM) 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 industry.
Our reputation for leading in the field of autonomous vehicle systems, applied artificial intelligence and control engineering has been established through more than thirty years of research into this field. We cover all types of autonomous vehicles including airborne, ground and marine as well as space.
About the Role
The Trustworthy Autonomous System (TAS) node in security is a collaborative 3.5-year grant with Lancaster University, examining the fundamentals of security in networked autonomous systems. At Cranfield, our focus is on 4 areas: the mission, the control, the networking, and the human-machine interface. We are recruiting another research fellow for this strategic EPSRC project to work under the umbrella of our general research vector in TAS with Lancaster.
Autonomous systems such as drones, self-driving cars and robots will become a familiar feature of our social environment as technologies develop. As part of this multidisciplinary research programme, the 2 year human-machine interface project recognises the tendency for Autonomous Systems security properties to generate adaptive behaviours, particularly around human machine control issues. Behavioural influences when interacting with autonomous systems will be investigated in order to understand the potential impact on system security. In particular, the research programme will explore behavioural adaptation under security breaches both in the field and laboratory. The successful candidate will investigate how unintended behaviours could have negative effects on safety and security. Questions such as ‘how do behaviours change with repeated exposure to an autonomous vehicle and how might these changes affect human responses to requests for the vehicle to take over?’ will be investigated. As Research Fellow you will be responsible for developing new assessments to profile these adaptive behaviours to develop protocols and standards for autonomous systems that are more secure.
You will be educated to doctoral level in a relevant subject (with a degree in Psychology or Psychology as a major component), and have experience of management research using both qualitative and quantitative methods. With excellent communication skills, you will have expertise in human factors and a background in analysing large data sets would be an advantage. You will also have a developing track record of publishing in high quality journals. Further information can be found here.
In return, the successful applicant will have exciting opportunities for career development in this key position, and to be at the forefront of world leading research and education, joining a supportive team and environment.
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. Find out about our key commitments to Equality, Diversity and Inclusion and Flexible Working here. We are currently piloting hybrid working arrangements until April 2022. This means the majority of our staff are spending between 40% and 60% of their time working from the office where job roles allow.
How to apply
For an informal discussion, please contact Dr Lisa Dorn, Associate Professor of Driver Behaviour, on (T); +44 (0)1234 758223 or (E); email@example.com
|Placed On:||13th October 2021|
|Closes:||31st October 2021|
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