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Research Fellow (Modelling and machine learning)

School of Veterinary Medicine

Location:  Guildford
Salary:  £32,817 to £33,797 per annum
Fixed Term until 01/07/2022
Post Type:  Full Time
Advert Placed:  Monday 16 December 2019
Closing Date:  Wednesday 22 January 2020
Interview Date:  Wednesday 12 February 2020
Reference:  099319

Principal Investigators: Dr Gianni Lo Iacono, Professor Payam Barnaghi, Professor Roberto La Ragione

We are excited to invite applications for a Research Fellow position funded by the EU, as part of a new European Framework integrating veterinary, medical and environmental health research (One Health EJP - https://onehealthejp.eu/).

We are seeking a full-time Postdoctoral Research Fellow in modelling and machine learning applied to the rising problem of antimicrobial resistance.

The post is part of the One-Health EJP consortium, an EU funded partnership between 39 partners, including acclaimed food, veterinary and medical laboratories and institutes across Europe and the Med-Vet-Net Association (https://onehealthejp.eu/).

The consortium aims is to enhance the prevention, detection and control of zoonoses and antimicrobial resistance. To achieve this goal you will formulate and apply mathematical models in conjunction with the development of next-generation AI. The post is for a full-time researcher for 30 months, to start as soon as possible.

The successful applicants will work across different units: the department of Veterinary Medicine and Public Health and the Department of Pathology and Infectious disease at the School of Veterinary Medicine and the Machine Learning for Healthcare Research group at the Centre for Vision, Speech and Signal Processing (CVSSP).

The research at the School of Veterinary Medicine is at the forefront to tackle one of the most serious, global, threat that our society is facing: the rising of antimicrobial resistance (AMR). Antimicrobials are used in human and veterinary medicine and they are important tools for the treatment of infections. However, the emergence of widespread antimicrobial resistance AMR is threatening our ability to treat and control even the most simple of infections. AMR is the ability of a microorganism to withstand the effects of an antibiotic or other compound. AMR can be driven through selective pressures such as the inappropriate use of antimicrobials and can be transferred from one pathogen to another through the exchange of genetic material. In line with the One Health philosophy, our research is highly multi-disciplinary and multi-institutional.

Past research in healthcare at CVSSP has resulted in a software system with integrated machine learning algorithms (Class 1, medically certified system) which is currently being offered as a pilot service by the Surrey and Borders NHS Trust at the National Health Service (NHS) - this was the outcome of our TIHM for Dementia project. The group’s research has received several awards including New Health Tech Innovation of the Year award in the Health Tech Digital Awards 2019, HSJ 2018 Award for Improving Care with Technology and an NHS Regional Parliamentary Award.

You will be responsible for research into mathematical modelling, machine learning, time-series data analysis and probabilistic and mechanistic models. The role will suit a highly motivated candidate who is interested in addressing real-world challenges. In particular you shall use novel rigorous approaches to investigate the links between antimicrobial usage in animals, antimicrobial resistance in the environment, and the risks for public health.

You should have a relevant PhD/DPhil (or be near completion), in addition to holding a first degree in engineering, physics, computer science, mathematics, statistics or similar. Experience in software development and programming, as well as in practical applications of adaptive algorithms in working with uncertain data will be highly desirable. You should have a track record of published work with experience of working well independently and also as part of a team. You will be expected to develop your solutions in one of Python, MATLAB or R.

You will join established research groups within the consortium with a strong track record and excellent research infrastructure. As a Bronze Athena SWAN award holder, Stonewall Diversity Champion and Disability Confident employer, we are committed to supporting equality, diversity and inclusion.

For informal enquiries please contact Dr Gianni Lo Iacono (g.loiacono@surrey.ac.uk) or Professor Payam Barnaghi (p.barnaghi@surrey.ac.uk).

To apply on-line please go to our website at: https://www.surrey.ac.uk/working-at-surrey

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Further details:

For more information and to apply online, please download the further details and click on the 'apply online' button above.

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Athena Swan Bronze Award / Disability Confident Committed / Stonewall Diversity Champion