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Impacts of individual level variation on computational models of evolutionary and epidemiological invasion


Project Description

Countries are at increasing risk of invasions and incursions from exotic
pathogens. In recent years we have seen the devastating impacts of, for
example, ash dieback on native Ash, the Asian hornet on honey bees and Avian
Influenza on the poultry industry. As well as creating potentially serious damage
to the native ecosystem and its natural capital this can also have quite serious
socio-economic impacts. By their very nature, it can be hard to predict the likely
spread and penetration of exotic pathogens due to the lack of previous
exposure and knowledge. For this reason mathematical modelling is a crucial
tool in assessing the likelihood and the seriousness of any potential event.
In collaboration with the Animal and Plant Health Agency (APHA) the student
will develop computational models to further our epidemiological
understanding of how pathogens can spread by examining in detail the
behavioural interactions of the host or reservoir species of the pathogen,
specifically the role of individual heterogeneity. The collaboration with APHA,

and the National Wildlife Management Centre (NWMC) in particular, will
provide the student with unparalleled access to datasets which are both
extensive and topical and provide a unique opportunity to parameterise and
compare to existing government models. Our initial case study will focus on the
red fox and its potential to harbour rabies. However, there will be an
opportunity for the student to influence the choice of additional case studies
within the interests of APHA and the ACCE DTP.
As part of the project the successful candidate will spend a period of time
working within APHA (at Sand Hutton near York) where they will be expected to
interact with the wildlife team and engage in ongoing research projects relevant
to the PhD. This will provide an exciting opportunity for the student to
experience the process of developing research for policy and gain insight into
the current priorities of UK government.
The Candidate
Applicants should have or expect to achieve at least a 2.1 honours or equivalent
degree in Biology, Mathematics or related subject. They will demonstrate strong
interest and self-motivation in the subject, good computational skills (ideally
knowledge of programming in C++ or Python), an ability to think analytically and
creatively. Good presentation and writing skills in English are required. Previous
research experience in contributing to a collaborative interdisciplinary research
environment is highly desirable but not necessary as training will be provided.

Funding Notes

Funding: This is a 3.5 year fully-funded studentship part of the NERC Doctoral Training Partnership in Adapting to the Challenges of a Changing Environment (ACCE). The studentship covers: (i) a tax-free stipend at the standard Research Council rate (around £15,000 per year), (ii) tuition fees at UK/EU rate, (iii) research consumables and training necessary for the project.

Entry requirements: At least an upper second class honours degree, or equivalent in any relevant subject that provides the necessary skills, knowledge and experience for the DTP, including environmental, biological, chemical, mathematical, physical and social sciences.

References

Eligibility: The studentships are available to UK and EU students who meet the UK residency requirements. Students from EU countries who do not meet the residency requirements may still be eligible for a fees-only award. Further information about eligibility for Research Council UK funding

Shortlisting: Applicants will be notified if they have been selected for interview in the week commencing on Monday 28 January 2019.

Interviews: Shortlisted applicants will be invited for an interview to take place in the Department of Biology at the University of York in the week beginning 11 February 2019 (or the following week). Prior to the interview candidates will be asked to give a 5 minute presentation on a research project carried out by them.

How good is research at University of York in Biological Sciences?

FTE Category A staff submitted: 44.37

Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities

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