Fully funded studentship available for entry in October 2024
This 4-year PhD studentship provides inter-disciplinary training at the intersection of population genetics, evolution, and synthetic biology, with a focus on mathematical modelling, statistics, and computational methods.
The student will be an active member of Target Malaria, a unique research consortium developing novel genetic methods to control the mosquitoes that transmit malaria.
The student will be based in the Department of Life Sciences at the Silwood Park campus of Imperial College, a leading international centre for research and teaching in ecology, evolution, and conservation, and will have the opportunity to join the Science and Solutions for a Changing Planet DTP.
Context
Vector-borne diseases continue to impose a tremendous burden on human populations, and new interventions to reduce transmission and eliminate the diseases are badly needed. The worst is malaria, which causes hundreds of thousands of deaths every year, mostly of infants and children, mostly in Africa. One promising new approach uses synthetic gene drive constructs to genetically alter the vector population, either interfering with their reproduction (so as to suppress the population) or blocking their ability to transmit the parasite.
The project
The project will involve modelling the spread of gene drive constructs in mosquito populations. Depending upon the aptitudes and interests of the student, the project may involve
(1) estimating key demographic parameters like dispersal rates, aestivation probabilities, and population size fluctuations from genomic data;
(2) assessing alternative genetic strategies to minimise the likelihood that resistance evolves;
(3) developing optimal release and monitoring regimes; and/or
(4) other relevant topics.
Depending on the exact topics chosen, the student will have the opportunity to learn (or expand their proficiency in):
(1) population genetic dynamical systems modelling, including across a landscape (analytical theory and simulations, with coding e.g., in Julia and/or Mathematica); and/or
(2) demographic inference from population genomic data (e.g., using SLiM and/or Approximate Bayesian Computation)
More generally, a skills and training plan will be developed, with opportunities to audit relevant modules at Imperial or attend courses externally.
Prior knowledge in these areas is not necessary -- training will be provided -- but an eagerness to learn is.
Eligibility
Applicants should have, or expect to achieve, a first or upper second-class degree in a relevant subject, which includes all of those from the quantitative and life sciences – including biology, zoology, genetics, mathematics, physics, computer science, and statistics.
Funding
This 4-year studentship provides generous support, including a tax-free stipend at the Wellcome Trust's London rate (currently £24,975 in year 1 and rising to £26,839 in Year 4). Funding also covers tuition fees up to the UK home student rate.
Target Malaria
The student will join a multi-disciplinary international consortium of over 200 researchers at 7 different institutions around the world bringing together experts in molecular and population genetics, field entomology, ecology, epidemiology, risk analysis, regulatory science, stakeholder engagement, and project management (for further details, see www.targetmalaria.org). We receive core funding from the Bill & Melinda Gates Foundation and the Open Philanthropy Project.
Application procedure
To apply, in the first instance please send a CV (including names of two references) and cover letter (including why you want to do a PhD and why you are interested in this particular project) in a single PDF document to [Email Address Removed].
Deadline
Closing date for applications: 5 Jan 2024.
Further opportunities
Opportunities to join this program can also be accessed through the NERC DTP, and interested applicants are encouraged to apply by this route as well (deadline 8 Jan 2024 at noon).
Further information
Informal enquiries can be directed to [Email Address Removed].