PhD - Algorithms to better understand how zika has come about

University of East Anglia - School of Computing Science

Start Date: October 2017

No. of positions available: 1

Supervisor: Dr Katharina Huber

Project description: The emergence of antibiotics resistance in bacteria and new organisms such as the zika virus [i] has major ramifications for public health. An important steppingstone in the development of strategies to combat them is to understand how they have evolved. The development of powerful algorithms and software tools to describe and understand the evolution of species, populations and individuals is one of the foci of the burgeoning area of phylogenetics which lies at the interface of molecular biology and computer science.

Firmly embedded within computer science, the PhD project is concerned with the development of cutting edge algorithms and software for phylogenetic network reconstruction (essentially rooted directed acyclic graphs) [ii]. It combines elements from phylogenetic supertree reconstruction [iii] with the expertise of the supervisor (see e.g. [iv] and [v] and, more generally, the supervisor's website at The successful applicant will have a good background in computer science or a related area. Biological knowledge is however not required. Informal enquiries concerning the project are welcome by the supervisor (

Interviews will take place between 16 January and 24 February 2017.

Person specification:  Students must have at least a 2:1 in computer science or a related area.

Funding notes: This PhD project is in a Faculty of Science competition for funded studentships. These studentships are funded for 3 years and comprise home/EU fees, an annual stipend of £14,296 and £1000 per annum to support research training. Overseas applicants may apply but they are required to fund the difference between home/EU and overseas tuition fees (in 2016/17 the difference is £12,879 for the Schools of CHE & PHA, and £9,679 for CMP & MTH but fees are subject to an annual increase)

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South East England