The School of Biological and Behavioural Sciences at Queen Mary is one of the UK’s elite research centres, according to the 2021 Research Excellence Framework (REF). We offer a multi-disciplinary research environment and have approximately 180 PhD students working on projects in the biological and psychological sciences. Our students have access to a variety of research facilities supported by experienced staff, as well as a range of student support services.
Our PhD students become part of Queen Mary’s Doctoral College which provides training and development opportunities, advice on funding, and financial support for research. Our students also have access to a Researcher Development Programme designed to help recognise and develop key skills and attributes needed to effectively manage research, and to prepare and plan for the next stages of their career.
Knowledge of the extent to which recent adaptation shaped genomic architecture is crucial to understanding how environmental and lifestyle changes affected the evolutionary history of species. The resurgence in artificial intelligence, and in particular the advent of deep learning algorithms, has fueled a paradigm shift in predictive modeling for learning about neutral and adaptive evolution. Our group pioneered the use of convolutional neural networks on haplotype alignments for population genetic inferences (eLife, 2021, see figure).The objective of this proposal is to introduce a suite of deep learning tools for studying recent and fluctuating natural selection from temporally and spatially sampled genomic data. Notably, these methods will account for the many technical challenges encountered in both model and nonmodel study systems. Specifically, we will design predictors for detecting signals and learning parameters of selection from incomplete, low-quality, and unphased ancient samples, using approaches that circumvent the uncertainty in genetic and demographic parameters, and that extend to data generated by cost-efficient low-coverage and pooled sequencing strategies.
With the co-supervisor Dr Oostra, we propose several applications to empirical data sets to illustrate the power of our methods and discover novel biological insights. Specifically, we propose to detect recent selection in disease vectors, such as malaria- and yellow fever-carrying mosquitoes, and other species known to have been subjected to fleeting selection due to environmental pressure, or from museum specimen.
Notably, impact will be enhanced by implementing dedicated software with the external collaboration of Dr Michael DeGiorgio, our partner at Florida Atlantic University.
This studentship is open to students applying for CONACyT funding. CONACyT will provide a contribution towards your tuition fees each year and Queen Mary will waive the remaining fee. CONACyT will pay a stipend towards living costs to its scholars. Further information can be found here: https://conacyt.mx/convocatorias/convocatorias-becas-al-extranjero/
Please refer to the CONACyT website here: https://conacyt.mx/convocatorias/convocatorias-becas-al-extranjero/ for full details on eligibility and conditions on the scholarship.
Applications are invited from outstanding candidates with or expecting to receive a first or upper-second class honours degree in an area relevant to the project including, but not limited to, biology, statistics, or computer science. A masters degree is desirable, but not essential.
Applicants from outside of the UK are required to provide evidence of their English language ability. Please see our English language requirements page for details: https://www.qmul.ac.uk/international-students/englishlanguagerequirements/postgraduateresearch/
Informal enquiries about the project can be sent to Matteo Fumagalli at m.fumagalli@qmul.ac.uk
Applicants will need to complete an online application form to be considered, including a CV, personal statement and qualifications. Shortlisted applicants will be invited for a formal interview by the project supervisor. Those who are successful in their application for our PhD programme will be issued with an offer letter which is conditional on securing a CONACyT scholarship (as well as any academic conditions still required to meet our entry requirements).
Once applicants have obtained their offer letter from Queen Mary they should then apply to CONACyT for the scholarship as per their requirements and deadlines, with the support of the project supervisor.
Only applicants who are successful in their application to CONACyT can be issued an unconditional offer and enrol on our PhD programme.
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