This exciting 24 month position will give you the opportunity to work on an extremely interesting, varied and challenging role helping to achieve the partnership’s objectives.
VCA Technology and Kingston University are working together to develop a computer vision solution based on deep learning to accurately detect and count people in highly dense and cluttered scenes.
You will also have the support of Kingston University academic experts based in The Faculty of Science, Engineering and Computing, the University’s KTP Team and a KTP Advisor.
You will be working as part of a team on developing a computer vision solution based on deep learning to accurately detect and count people in highly dense and cluttered scenes. This is a KTP position which not only provides the opportunity to work with both academics and industry but also provides significant training and development opportunities.
The successful candidate will be based at VCA Technology Ltd offices in Chessington. VCA Technology is a leader in embedded intelligent video systems. We’ve deployed over 350,000 channels of embedded video analytics which detect intruders and count people on low power ARM devices. We have a highly skilled team of software developers and computer vision engineers who follow an Agile Scrum process including all of the associated best practices such as TDD (Test Driven Development), cross-platform CI (Continuous Integration) and daily scrums. www.vcatechnology.com
Although, you are likely to spend some time in the School of Computing at Kingston University, where the academic team is based. The multidisciplinary Robot Vision research Team (RoViT), led by Prof. Paolo Remagnino, is one of the main research groups of the Computer Science department and one of the most successful multidisciplinary teams of the Faculty. www.kingston.ac.uk
We are seeking a natural problem solver with extensive experience in the application of deep learning for computer vision applications to lead this project and embed deep learning capabilities within the organisation.
Qualifications and experience requirements
For a full list of requirements please see the job description:
- PhD or Master’s degree with demonstrable practical experience of the application of deep learning techniques to solve
- Practical experience of implementing and training deep neural networks for computer vision applications
- Practical experience with deep learning frameworks and tools such as Caffe, Theano, Tensorflow, etc
- Practical experience with computer vision
- Proficient at programming in C++ and/or Python
Accepted degree subjects
computer sciences and IT
£33k to £39,000
depending on qualifications and experience plus training package of £4,000
Contract and working hours
How to apply
Number of vacancies: One
About KTP: This position forms part of the Knowledge Transfer Partnership (KTP) programme funded by Innovate UK and is one of the UK’s leading graduate recruitment programmes, offering the opportunity to take part in strategic and innovative projects while gaining valuable workplace experience on specific projects of strategic importance to partner companies It is essential you understand how KTP works with the business and the University, and the vital role you will play if you successfully secure a KTP Associate position.
To discuss this opportunity informally please email stating clearly the vacancy number that you are interested in.
Closing date: 11/05/2017
This job listing will no longer be available on Prospects from 11/05/2017