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 18 Months
Salary £24,739
Apply by 22/03/2020 

Role Description

We welcome applications from those interested in an exciting Research Assistant post, with a good background in Computer Vision and Artificial Intelligence. A wide knowledge of computing algorithms and programming languages is also essential.

As the UK’s only exclusively postgraduate university, Cranfield’s world-class expertise, large-scale facilities and unrivalled industry partnerships is creating leaders in technology and management globally.  Our distinctive expertise is in our deep understanding of technology and management and how these work together to benefit the world.

Our people are our most valuable resource and everyone has a role to play in shaping the future of our university, developing our learners, and transforming the businesses we work with. Learn more about Cranfield and our unique impact here: Working life at Cranfield.

Our shared, stated values help to define who we are and underpin everything we do: Ambition; Impact; Respect; and Community. To find out more please visit our website: https://www.cranfield.ac.uk/about/about

Cranfield Manufacturing is one of the eight themes at Cranfield University offering world-class and niche post-graduate level research, education, training and consultancy. We are unique in our multi-disciplinary approach by bringing together design, materials’ technology and management expertise. We link fundamental materials research with manufacturing to develop novel technologies and improve the science base of the manufacturing research. Our capabilities are unique, with a focus on simulation and modelling, and sustainability.  They also include work in composite manufacture, metallic glasses, nano-materials (graphene, coatings and sensors), low energy casting, thermal barrier coatings and Wire Arc Additive Manufacturing (WAAM).

An exciting opportunity has arisen for a Research Assistant to join the AI enabled Anomaly Detection (AIAD) Group to work on an Innovate UK funded project. The project addresses the need of reducing the construction disputes in the UK via the development of a 'system of work' for contracts and warranty/assurance administration. This system of work will be supported by an integrated 'one-source solution' which includes a set of digital technologies to enable activity monitoring on-site, and during the manufacture and assembly of components off-site. The work of this post covers the 1) engagement with the industrial partners to understand the technical requirements; 2) development of a set of algorithms with their software implementation for Personal protective equipment (PPE) detection, worker tracking and behaviour analysis and work progress measure using computer vision and artificial intelligence based approaches, 3) integration and testing of the developed software with hardware, supported by an industrial partner, 4) supporting dissemination and promotion of the project outcomes.

You will have a MSc (or close to completion) degree in Computer Science or related subjects with a good background in Computer Vision and Artificial Intelligence. A wide knowledge of computing algorithms and programming languages is also essential.

We are ideally searching for an individual looking to develop a career in industrial application, thereby demonstrating a commercial attitude to development. You will have willingness to adopt and follow professional practice in the production of software code.

For an informal discussion, please contact Dr Yifan Zhao, Senior Lecturer in Data Science on +44 (0)1234 754729 or (E); yifan.zhao@cranfield.ac.uk

At Cranfield we value Diversity and Inclusion, and aim to create and maintain a culture in which everyone can work and study together harmoniously with dignity and respect and realise their full potential. We actively consider flexible working options such as part-time, compressed or flexible hours and/or an element of homeworking. 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.

Our equal opportunities and diversity monitoring has shown that that women and minority ethnic groups are currently underrepresented within the university and so we actively encourage applications from eligible candidates from these groups.  To find out more, please visit https://www.cranfield.ac.uk/about/working-at-cranfield/diversity

For an informal discussion, please contact Dr Yifan Zhao, Senior Lecturer in Data Science on +44 (0)1234 754729 or (E); yifan.zhao@cranfield.ac.uk

Interviews to be held on: 25 March 2020