Research Fellow - AKT Associate (108826-0224)

The Visualisation Group at WMG are looking for a talented and highly motivated researcher to further our research on the development of machine learning methods on the development of anti-bacterial susceptibility testing in collaboration with Cytecom.

You will contribute to a developing project portfolio in applying AI solutions to engineering and computing problems. Our partners at Cytecom have created a diagnostic device that can determine the correct antibiotic choice, rapidly.

This project aims to create a smart solution via ML to analyse data from Cytecom’s current prototype; more accurately determining a bacterial sample’s health in exposure to antibiotics, making it a far more powerful diagnostic tool.

About Accelerated Knowledge Transfer (AKT)

This programme has been developed to create short-term collaborations between a Business and a UK Knowledge Base to rapidly inject innovation capacity and accelerate the evaluation or development of an innovation project or concept, which has the potential for significant impact for the Business.

AKT has been inspired by the highly successful partnership model of KTP (Knowledge Transfer Partnership) funded by Innovate UK. KTP is a UK-wide programme that has been helping businesses for the past 45 years to improve their competitiveness and productivity through the better use of knowledge, technology and skills that reside within the UK Knowledge Base. For further information visit http://ktp.innovateuk.org