Imperial College London Featured PhD Programmes
Aberdeen University Featured PhD Programmes
University of Hong Kong Featured PhD Programmes

RVC PhD Studentship: Using 'Big Data' to investigate the genetic basis of hyperthyroidism in cats


This project is no longer listed on and may not be available.

Click here to search for PhD studentship opportunities
  Prof H Syme, Dr L Davison, Dr Marsha Wallace  No more applications being accepted  Funded PhD Project (UK Students Only)

London United Kingdom Bioinformatics Genetics Veterinary Sciences

About the Project

Department: Clinical Science and Services


Project Summary:

Why is hyperthyroidism so common in cats but not in other species, such as the dog? And why are some pure-breeds, such as the Burmese, relatively protected? Clearly there is a genetic basis for disease development and this project plans to investigate this on a species, breed and individual level using multiple bioinformatic methods. This project will utilize pre-existing data to look for genetic variation and transcriptomic changes within individual thyroid glands (using RNA-sequencing), use genome-wide association studies (GWAS) to compare hyperthyroid and euthyroid cats, and use genome discordance and conservation analysis to look for differences in thyroid-relevant genes among species with different susceptibility to hyperthyroidism. The results of these studies will provide insights into the genetic basis of this disease and so generate new hypotheses as to its pathogenesis and possible treatment targets.

The successful candidate will receive bioinformatic training for the analysis and interpretation of genetic data (RNA-sequencing, GWAS and whole-genome), as well as online lectures, tutorials, and exercises, tailored to the stage of the PhD project. They will also be trained in lab-based genetic techniques (DNA & RNA extraction, sequencing, RT-PCR etc.) and be involved in generation of clinical data through participation in research clinics (see below). Although not a direct component of this project, through the research group they will be exposed to work being done by others including clinical trials, cell culture, development of clinical tests (ELISAs, other analytical methods), and standard laboratory techniques (Western blotting, immunohistochemistry, etc.).


The ideal candidate will be a numerically and emotionally intelligent veterinary surgeon that is equally at home developing skills in statistical genomics on the computer or interacting with a cat owner. Although advanced knowledge of programming or bioinformatics is not expected, an aptitude for working with large data sets and genuine enthusiasm for learning how to program and working with a high-performance computer cluster is required. Alongside bioinformatic and laboratory work, the successful applicant will be required to participate in a first-opinion clinic that generates clinical samples (blood samples, post-mortem tissue collection) for research projects into the diseases of older cats; hyperthyroidism, hypertension CKD.

Although it is envisaged that the candidate can be primarily based in a single location (either Oxford or central London), and can also do most of the bio-informatics work remotely, some travel to the second site (either central London for clinics, or Oxford for benchtop genetics) will be required. An individualized plan will be agreed with the successful candidate. 


  • Must meet our standard PhD entry requirements
  • Veterinary surgeon (MRCVS)
  • Interest in, and aptitude for, pursuing bioinformatics training


  • While not essential, applications from veterinary surgeons that have completed an internship, residency or a certificate are particularly encouraged
  • Experience in a research environment, or experience undertaking bioinformatic or statistical analysis is desirable, but not essential

This project uses material (blood and tissue samples) collected from cats with naturally-occurring disease collected during routine clinical practice, as well as genetic data that is in the public domain.

This is a 3 year fully-funded studentship by Beryl Evetts and Robert Luff Animal Welfare Trust and the RVC. This studentship is open to applicants eligible for "Home" fees. International applicants are welcome to apply but must be able to fund the difference between "Home" and "Overseas" tuition fees. 

Please note that EU/EEA and Swiss national students may no longer be eligible for the “Home” rate of tuition fees, dependent on personal circumstances (including immigration status and residence history in the UK) and UK government rules which are currently being developed. For up-to-date information on fees for EU/EEA and Swiss national students following Brexit please see our fees and funding page.

The studentship will ideally commence 1st October 2021, and the funding will cover fees and a stipend.  

If you are interested in applying for this position, please follow the link below. Please use your personal statement to demonstrate any previous skills or experience you have in using both qualitative and quantitative research methods or computer programming experience.

How to Apply

For more information on the application process and English Language requirements see please see How to Apply.

Interviews will take place remotely over zoom.

We welcome informal enquiries - these should be directed to Harriet Syme ([Email Address Removed])

Deadline: Sunday 22nd August 2021 


1. Crossley VJ, Debnath A, Chang YM, et al. Breed, Coat Color, and Hair Length as Risk Factors for Hyperthyroidism in Cats. J Vet Intern Med 2017;31:1028-1034.
2. J. Aguiar, T. Hiron, R. Fowkes, H. Syme, L.J. Davison (2020) RNA transcriptomic analysis as a novel in vitro hypothesis- generating tool to unravel the pathogenesis of feline hyperthyroidism. In Research Communications of the 30th ECVIM-CA Online Congress. Journal of Veterinary Internal Medicine 34 (6): 3088.
3. Lau LW, Ghaznavi S, Frolkis AD, Stephenson A, Robertson HL, Rabi DM, Paschke R. Malignancy risk of hyperfunctioning thyroid nodules compared with non-toxic nodules: systematic review and a meta-analysis. Thyroid Res. 2021 Feb 25;14(1):3
Search Suggestions
Search suggestions

Based on your current searches we recommend the following search filters.