The Department of Mathematics at the University of Sussex is inviting
applications for a fixed-term research position on ecological modelling
of tick-borne pathogens to better understand their distribution and
prevalence along urbanisation and environmental gradients.

In this role, you will develop mathematical models to evaluate the
roles of multiple mechanisms in structuring ecological metacommunities
composed of ticks, their hosts and associated pathogens. Working closely
with project partners, you will integrate process-based metapopulation
models into network models to identify key environmental and social
determinants of the risk of human infection, and suggest critical points
for management actions.

The role includes research collaboration with the University of Bath (UK)
and a US team coordinated by researchers at Columbia University. While
this post has the fixed duration of 24 months, there will be an
opportunity to apply for a continuation of this position to be based at
the University of Bath (UK) for an additional 24 months of the project.

Apply here:
https://www.jobs.ac.uk/job/DQZ005/research-fellow-in-mathematics

*About you*
We are seeking a candidate with a strong background in mathematical
biology, ecological and/or epidemiological modelling, or applied
dynamical systems.

Prospective candidates should hold a PhD in Mathematics or be in the final
stages of writing up their PhD thesis and have submitted by the start date
of the position. Equivalent research experience will also be considered.
You should have familiarity with handling large and complex datasets,
and be skilled in programming languages such as Python, Matlab or R.

The ideal candidate will be capable of independent research as
well as effective teamwork, with excellent communication skills for
interdisciplinary engagement with colleagues and external collaborators. A
strong interest in interdisciplinary research and applying mathematical
techniques to ecological data and environmental challenges is highly
desirable.

*Further Key Information*
Please contact Prof Konstantin Blyuss (k.blyuss@sussex.ac.uk) for
informal enquiries.

Candidates should include in their application the following:

   - Academic CV
   - A personal statement (500 words maximum) outlining their research
     interests and their research experience to date
   - Official academic transcripts
   - Contact details for two suitable referees
   - Application form

For full details and how to apply see our vacancies page
<http://www.sussex.ac.uk/about/jobs>.

*Eligibility*

This role has been assigned an eligible SOC code and meets the salary
requirements for Skilled Worker Sponsorship if full time and appointed
at Grade 7.4.

Please consult our Skilled Worker Visa information page
<http://www.sussex.ac.uk/humanresources/business-services/visa/salary-requirements-tradeable-points>
for further information about Visa Sponsorship.

This role may also be eligible for the Global Talent visa route, depending
on the individual circumstances of the successful candidate.

Please note that this position may be subject to ATAS clearance
<https://www.gov.uk/guidance/academic-technology-approval-scheme> if
you require visa sponsorship.

The University requires that work undertaken for the University is
performed in the UK.

Sophia Bulzoni <smb2392@columbia.edu>

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