CRANFIELD UNIVERSITY

Research Fellow in Adversarial Machine Learning for Transportation (EPSRC MACRO)

Location
Cranfield, United Kingdom
Salary
£33,809 to £37,684 per annum, with potential progression up to £47,105 per annum
Posted
01 Sep 2021
End of advertisement period
03 Oct 2021
Ref
3744
Contract Type
Fixed Term

School/Department School of Aerospace, Transport and Manufacturing
Based at Cranfield Campus, Cranfield, Bedfordshire
Hours of work 37 hours per week, normally worked Monday to Friday. Flexible working will be considered.
Contract type Fixed term contract
Fixed Term Period 15 Months
Salary Full time starting salary is normally in the range of £33,809 to £37,684 per annum, with potential progression up to £47,105 per annum
Apply by 03/10/2021

Role Description

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.

We welcome applications from prospective Research Fellows in Adversarial Machine Learning for Transportation. This exciting role is part of a larger project is funded by EPSRC.

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.

About the Role

Our reputation for leading in the field of digital systems: sensor data, communications, machine learning, and reasoning - has been established through more than thirty years of research into this field. We are primarily focused in this project on secure AI/ML for transportation and mobility as a service (MaaS).  Our work covers academic provision (MSc and PhD) and research. Research works span from fundamental research and development to single client contract research and development.

As Research Fellow you will contribute to the research activities of the Centre for Autonomous and Cyberphysical Systems, especially concerning the specific activities of: (1) machine learning for transportation sector (especially in mobility as a service), (2) adversarial attack modelling in AI/ML, and (3) co-designing secure AI systems in mobility as a service sector.

About You

You will be expected to collaborate with the existing staff working in the same EPSRC project and the area and have communications and meetings with our collaborators within the university, the industrial / government partners, or in other universities.

You will be educated to doctoral level in a relevant subject and have experience of management research using both qualitative and quantitative methods. With excellent communication skills, you will have expertise in social network analysis and a background in Health & Safety would be an advantage. 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

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.

Diversity and Inclusion

Our equal opportunities and diversity monitoring has shown that women are currently underrepresented within the university and so we actively encourage applications from eligible female candidates.  To further demonstrate our commitment to progressing gender diversity in STEM, we are members of WES & Working Families, and sponsors of International Women in Engineering Day.

Flexible Working

We actively consider flexible working options such as part-time, compressed or flexible hours and/or an element of homeworking, and commit to exploring the possibilities for each role. Find out more here.

How to Apply

Please do not hesitate to contact us for further details on E: hr@cranfield.ac.uk. Please quote reference number 3744.

Closing date for receipt of applications: 3 October 2021

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