CRANFIELD UNIVERSITY

Research Assistant in Computer Vision and Embedded Systems

Location
Cranfield, United Kingdom
Salary
Full time starting salary is normally in the range of £24,739 per annum
Posted
Tuesday, 25 May 2021
End of advertisement period
Tuesday, 22 June 2021
Ref
3645
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 12 months
Salary Full time starting salary is normally in the range of £24,739 per annum
Apply by 22/06/2021

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.

Cranfield University, School of Aerospace, Transport and Manufacturing (SATM), Centre for Autonomous and Cyber-Physical Systems welcomes applications from Researchers in Computer Vision and Embedded Systems.

About Aerospace

Cranfield Aerospace is one of the eight major themes at Cranfield University. The Centre for Autonomous and Cyber-Physical Systems is a specialist centre established over 15 years within the School of Aerospace, Transport and Manufacturing dedicated to research and teaching in autonomous and space systems. We cover all types of autonomous vehicles including airborne, ground and marine as well as autonomous space exploration.

About the Role

This is a fixed-term position to support delivery of research on Autonomy and Air Mobility utilising Multi-User Environment for Autonomous Vehicle Innovation (MUEAVI) track within the Centre for Autonomous and Cyber-Physical Systems (A&CPS).

The research aim is to develop and validate new MUEAVI track capabilities supporting research projects in the areas of Intelligent Transport Systems, Autonomy, Navigation and Communication for Autonomous Systems. As Research Assistant you will be developing and implementing into hardware algorithms for multi-sensor fusion, object detection and localization, tracking using LIDAR, EO/IR, multi-spectral sensors with support from inertial and satellite navigation systems (IMU, GNSS). You will be also supporting testing and validation activities utilising MUEAVI capabilities for delivery of research projects.

About You

You will have an MSc in a relevant engineering discipline, such as computer vision, multi-sensor fusion or target tracking for autonomous systems with experience in dealing with object detection and classification from vision-based sensors (LIDAR, EO/IR, multi-spectral) with sensor fusion. Excellent communication skills, including the ability to communicate clearly at a technical, scientific level are essential.

You will also have experience in time-management, be able to work both independently and as part of a team and be experienced in carrying out modelling and simulation for autonomous systems.

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 and minority ethnic groups are currently underrepresented within the university and so we actively encourage applications from eligible candidates from these groups.

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

For an informal discussion about this opportunity, please contact Dr Ivan Petrunin, Lecturer in Digital Signal Processing for Autonomous Systems and DARTeC Fellow, on +44 (0)1234 750111 Ext. 8262 or i.petrunin@cranfield.ac.uk