AI/Vision Researcher in Railway Trackside Vegetation Management (KTP Associate)

AI/Vision Researcher in Railway Trackside Vegetation Management (KTP Associate)
£33,100 - £40,200 per annum

School of Computer Science and Electronic Engineering

KNOWLEDGE TRANSFER PARTNERSHIPS

Knowledge Transfer Partnerships (KTPs) are government-funded collaborations between universities and businesses. In KTPs, academics and company representatives jointly supervise a KTP Associate who is based in the company, with the goal of improving their competitiveness and productivity. KTPs serve to make better use of the knowledge, technology and skills generated by universities, colleges and research organisations.

Further information is available at: www.ktponline.org.uk

THE PROJECT

The University of Essex in partnership with Railscape Limited offers an exciting opportunity to build an intelligent vision system based on Machine Learning algorithms, which can accurately identify various features of trackside vegetation, including plant species and specimen health.

This post is fixed term for 24 months and is based at Railscape Limited offices in Rayleigh, Essex.

DUTIES OF THE POST

The duties of the post will include:

• Developing a vision system which can cope with significant variance caused by weather conditions and seasonal growth
• Exploring the state of the art and identifying the most appropriate Machine Learning approach based on e.g. convolutional neural networks, or more traditional approaches such as Random Forest
• Developing data visualisations using techniques such as guided gradient-weighted class activation mapping
• Building a semi-automated labelling system to classify features within the data
• Guiding on hardware selection for best data capture e.g. photogrammic, multispectral or hyperspectral
• Testing and evaluating the model using an agreed framework

• Working with colleagues and reporting to supervisors at Railscape
• Working with KTP partners on a regular basis
• Delivering a solution to the KTP project
• Integrating the solution with Railscape’s existing hardware and software infrastructure

KEY REQUIREMENTS

The post holder must have:

• BSc in Computer Science, Mathematics or a related discipline
• Higher degree in Computer Science, AI, Machine Learning or a related discipline, or equivalent experience
• A thorough understanding of the key methodologies and approaches in the field of computer vision
• Experience with machine learning and computer vision techniques
• Experience with/ strong Python programming skills
• Basic understanding of, or interest in plant science/biological science
• Basic understanding of, or interest in mechatronics
• Software development and data management skills
• The ability to devise innovative solutions to problems
• The ability to write clearly for both technical readers and general audiences

A full list of requirements can be found within the jobpack attached.

LOCATION

15 Totman Crescent

Rayleigh

Essex

England

SS6 7UY 

At the University of Essex, internationalism and diversity is central to who we are and what we do. We are committed to being a cosmopolitan, internationally oriented university that is welcoming to staff and students from all countries, faiths and backgrounds, where you can find the world in one place.

To support this commitment we have our Global Forum , a staff-led network that promotes and celebrates the rich cultural diversity among Essex staff, and our Colchester campus based Faith Centre , which hosts regular services, meetings and events organised by our chaplains and faith representatives.

Please see the attached job pack, which contains a full job description and person specification which outlines the full duties, skills, qualifications and experience needed for this role plus more information relating to the post. We recommend you read this information carefully before making an application.  Applications should be made on-line, but if you would like advice or help in making an application, or need information in a different format, please contact [email protected]

*More information: Working at the University