MRC AIM Doctoral Training Partnership: School of Veterinary Medicine & Science

University of Nottingham

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Veterinary Medicine & Science
Location:  UK Other
Closing Date:  Friday 12 January 2024
Reference:  MED1975

MRC AIM Doctoral Training Partnership

The AIM (Advanced Inter-Disciplinary Models) DTP is funded by the MRC between three Partners – the Universities of Birmingham, Leicester and Nottingham – and three more Associate Partners – the Research Complex at Harwell, Mary Lyon Centre and Rosalind Franklin Institute. We have a range of exciting and diverse PhD 4-year projects at all 3 partner Institutions which are now open for a September 2024 start and those available at The University of Nottingham are detailed below.

Projects with an industry partner (iCASE projects) offer a unique opportunity to undertake translational research and come with a mandatory placement requirement and an enhanced stipend.

Full information about funding of these projects and application details, including application form, plus Equality, diversity and inclusion form are available at .

Application deadline

The deadline for submitting applications is Friday, 12 January 2024. Please ensure that your application is submitted with all required documentation by the above deadline as incomplete applications will not be considered. See full details at the “how to apply” section below. After the closing date, the project supervisors will review all applications submitted for their project and shortlist a maximum of two candidates for interview.

Shortlisted applicants will be contacted by 9 February 2024 via email. If applicants don’t receive an email by this date, then their application has not been shortlisted and they will not be invited for interview. Unfortunately, due to the number of applications the DTP receives, it will not be possible to provide feedback on unsuccessful applications.


Interviews will take place during the week commencing 26 February and will be held via Zoom.   Please ensure you are available for the whole week as we are unable to offer any alternative interview dates/times.

We strongly encourage you to contact the supervisor(s) of the project in which you are interested before submitting an application. 

As stipulated by the funders, recruitment for International candidates to the DTP is capped at 30% of the whole cohort.

Academic requirement

Applicants must hold, or be about to obtain, a First or Upper Second class UK honours degree, or the equivalent qualifications gained outside the UK, in a relevant subject. A master’s qualification in a related area could be beneficial, as could additional relevant research experience. 

More details can be found on the MRC website.

How to apply

Applications should include:

  • A completed application form
  • A CV consisting of no more than 2 sides of A4
  • A transcript of module marks
  • Completed ED&I form.

Please submit your application for University of Nottingham projects to [email protected] .

What happens after interview?

Candidates who are ranked highest at interview will be offered a place on the DTP and will be recommended for the PhD position. Successful candidates will then be sent details of how to make the formal application at the project host institution and will be subject to standard admissions checks which is standard procedure. The host institution admissions team will then send out formal offer letters and details of how to complete the registration process. The DTP Funding Team will send out formal funding award letters.

Projects open for application

School of Veterinary Medicine and Science

Project Title: Tackling the pandemic of antibiotic-resistant infections: An artificial intelligence approach to new druggable therapeutic targets and drug discovery

Supervisors: Tania Dottorini, [email protected] , Michelle Baker (UoN), Julie Morrissey (UoL), Stephan Heeb (UoN), Hany Elsheikha (UoN)


Antimicrobial resistance (AMR) poses a major global health threat. Among respiratory infections, Staphylococcus aureus and Pseudomonas aeruginosa caused around 360,000 and 139,000 deaths, respectively, due to antibiotic resistance. Unfortunately, there is a stark lack of new drugs in the pipeline to treat these resistant infections, making it imperative to research new targets. In this project, we will develop an artificial intelligence (AI) approach to discover potentially new S. aureus and P. aeruginosa druggable proteins and to identify lead drugs inhibiting the target by a deep learning approach fed with 3D modelling. Taking large genomic data sets we will use cutting edge AI approaches to identify genes linked to antibiotic resistance. We will then experimentally validate these using CRISPR/Cas9 and transcriptomics technologies. Finally for confirmed drugs targets we will identify and experimentally test, drug compounds that could be developed into new treatments for AMR infections. This project based within an international research group, is at the frontier of AMR research taking a multi-disciplinary approach to explore a full pipeline from bacterial sequence to drug discovery.

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