RVC Supervisor(s): Dr Daniel Goldhill, Professor Damer Blake

Department: Pathobiology and Population Sciences

Non-RVC Supervisors: Dr Damien Tully (LSHTM)

Background, aims and objectives:

The diversity of circulating influenza viruses in birds means that there is a constant risk that a novel virus could emerge and cause a future pandemic. However, most avian influenza infections in humans do not spread beyond a single individual as avian viruses are poorly adapted to human host factors. While the mechanisms of certain adaptive mutations are known1,2, we still cannot predict which avian viruses have a greater propensity to infect human cells. A better understanding of which mutations lead to human adaptation would aid in pandemic preparedness by highlighting which avian influenza viruses are likeliest to emerge.

Several computational studies have compared avian and mammalian influenza sequences to identify mammalian-adaptive mutations3. However, these studies rarely test whether identified mutations have the predicted biological effect3. Furthermore, as biological mechanisms are mostly unknown, it is impossible to establish which mutations are associated with particular host factors or to easily predict the effect of novel mutations.

This PhD project will implement a large-scale bioinformatic analysis of sequences of avian influenza infection from mammals to identify human adaptive mutations. Structural models will then be used to classify which mutations likely share a mechanism allowing for the discovery of mutations with unknown mechanism which could be interacting with novel host factors. Focusing on mutations in the polymerase, laboratory-based analyses using minigenome assays4 will be undertaken to assess whether these mutations lead to human adaptation. Furthermore, this work will identify novel host factors behind mutations of unknown mechanism1. Finally, a model encompassing the mutational repertoire across all genes will be constructed to predict the likelihood of human emergence for current and future circulating strains of avian influenza.

The student will benefit from a highly multidisciplinary supervisor team as you will be trained in complementary skills in bioinformatics, molecular virology and structural biology. This diverse skill set will equip you for a multitude of potential career paths. This project would suit a candidate with a background or experience in laboratory techniques/molecular biology and/or computational biology. Experience and prior knowledge of influenza may be advantageous but is not essential. We are supportive of diverse career paths and we welcome applicants with a diversity of backgrounds, experience and ideas and we encourage applications from those with non-traditional academic backgrounds as well as those who are not looking for a career in academia. Informal enquiries are welcome and may be addressed to the principal supervisor.


  1. Long, J. S. et al. Species difference in ANP32A underlies influenza A virus polymerase host restriction. Nature 529, 101-104 (2016).
  2. Pinto, R. M. et al. Zoonotic avian influenza viruses evade human BTN3A3 restriction. bioRxiv, 2022.2006.2014.496196 (2022). https://doi.org:10.1101/2022.06.14.496196
  3. Borkenhagen, L. K., Allen, M. W. & Runstadler, J. A. Influenza virus genotype to phenotype predictions through machine learning: a systematic review: Computational Prediction of Influenza Phenotype. Emerging microbes & infections 10, 1896-1907 (2021).
  4. Goldhill, D. H. et al. The mechanism of resistance to favipiravir in influenza. Proceedings of the National Academy of Sciences 115, 11613-11618 (2018).



  • Must meet our standard PhD entry requirements
  • Successful degree in biological or similar subject or a related veterinary degree
  • Self-motivated
  • Willing to learn dry lab and wet lab techniques
  • Collaborates with other students and contributes to a friendly and diverse laboratory environment


  • Practical experience in tissue culture/sterile working techniques and molecular biology 
  • Experience in working in R or Python

Award includes tuition fees (UK home fees only) and a stipend of £19,668 (non-vet) or £24,789 (vet) including London Weighting (at 2022/23 rates, so slightly higher for 2023 entry). Full time for 3 years, from October 2023. International applicants are welcome to apply but must be able to fund the difference between "Home" and "Overseas" tuition fees.

This studentship will be held jointly between the lab of Dr Daniel Goldhill, based at the beautiful Hawkshead Campus of the RVC, and Dr Damien Tully at the London School of Hygiene and Tropical Medicine in London.

Dr Daniel Goldhill is a lecturer in virology. He has previously worked on experimental evolution of bacteriophage with Prof. Paul Turner at Yale and experimental evolution of influenza with Prof. Wendy Barclay at Imperial College London. He uses experimental evolution to understand who viruses change in response to novel drugs and when they switch hosts.

Dr Damien Tully is a lecturer in Epidemiology, Biostatistics and Bioinformatics. He did his PhD on RNA virus evolution and has since published on HCV and HIV-1.

Further support to the studentship will be provided by Prof. Damer Blake (RVC, Hawkshead campus) who is an expert in parasite genetics.  

This project offers an exciting opportunity to work in two world-class research institutions combining bioinformatic and wet-lab research into influenza.

This project will start in October 2023.

If you are interested in applying for this position, please follow the link below.  Please use your personal statement to tell us why this project excites you, the sort of science that you are most interested in, and to demonstrate any previous skills or experience relevant to the project.

How to Apply

For more information on PhD's at the Royal Veterinary College, the application process and English Language requirements see How to Apply.

Interviews will take place March 2023.

Further details about the project and informal enquiries can be directed to the Lead Supervisor: dgoldhill@rvc.ac.uk or the Co-Supervisor: damien.tully@lshtm.ac.uk 

Deadline: 13/02/2023

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