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Research Fellow - AKT Associate (108826-0224)

University of Warwick - WMG

Qualification Type: PhD
Location: Coventry
Funding for: UK Students, EU Students, International Students
Funding amount: £33,966 to £44,263 per annum
Hours: Full Time
Placed On: 27th February 2024
Closes: 2nd March 2024
Reference: (108826-0224)

Duration: Fixed term Contract for 4 months

About the Role 

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 

About You 

You will have a PhD in Computer Science or a related field. Particularly, candidates should have experience in the following areas:

  • A solid foundation in deep learning methods including the computing and statistical principles that found it.
  • Experience of working with pyTorch (or similar) for solving real-world problems or advancing machine learning solutions.
  • The ability to process and handle data collected from diverse sensors.
  • A publication record that demonstrates the above.

For further information regarding the skills required for this role please see the personal specification section of the attached job description.

If you are near submission or have recently submitted your PhD but have not yet had it conferred, any offers of employment will be made as Research Assistant at the top of level 5 of the University grade structure. Upon receipt of evidence of the successful award of your PhD, you will be promoted to Research Fellow on the first point of level 6 of the University grade structure

Full details of the duties and selection criteria for this role can be found in the vacancy advert on the University of Warwick's jobs pages. You will be routed to this when you click on the Apply button.

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