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School of Biological and Behavioural Sciences

Efficient Bayesian HMC sampling for inferring evolutionary timescales using large genome datasets

We are seeking applicants for the following PhD opportunity. The successful applicant will join a student cohort in Environment, Biodiversity and Genomics, training together, following an exciting programme designed to inspire the next generation of environmental experts, managers and leaders. They will be equipped to address some of the toughest challenges of our time.

Research environment

The School of Biological and Behavioural Sciences at Queen Mary is one of the UK’s elite research centres, according to the 2014 Research Excellence Framework (REF). We offer a multi-disciplinary research environment and have approximately 150 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.

Research in the dos Reis Lab focuses on the development and application of statistical methods in phylogenetics. In particular, we use Bayesian statistics to model evolutionary processes for the analysis of Big Genomic Datasets. We have applied our methods to study virus evolution, protein translation and evolution, genome evolution, and estimating the timeline of diversification of Life on Earth. We have been very successful in developing software and models that are widely used by the worldwide scientific community to anwer important questions in evolutionary biology.

Project description

In this project the student will develop software implementing a Hamiltonian Monte Carlo sampler to analyse big genome data to infer evolutionary timescales. Hamiltonian Monte Carlo borrows methodologies from statistical mechanics for efficient sampling of posterior distribuitons which are modelled as potential energy landscapes.

The methodology will be validated by large-scale computing simulations of genomes evolving along evolutionary trees and will be applied to resolve outstanding questions on evolutionary timescales of Life on Earth, such as the impact of he K-Pg and PTEM extinction/diversification on life difersification and relationship to past-climate changes. The methodology will also be extended to analyses of large viral evolutionary trees to extract information on phylodynamic patterns of spread, mutation and adaptation.

Training and development

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.

The student will develop their computing programming skills (such as C, C++, R package development, and high-performance computing), statistical analysis of Big Data (maximum likelihood, Bayesian inference, Bayesian model selection, Hamiltonian Monte Carlo sampling) and genomics (genome evolution, population genetics, natural selection, and phylogenetics).


This studentship is open to students applying for China Scholarship Council funding. Queen Mary University of London has partnered with the China Scholarship Council (CSC) to offer a joint scholarship programme to enable Chinese students to study for a PhD programme at Queen Mary. Under the scheme, Queen Mary will provide scholarships to cover all tuition fees, whilst the CSC will provide living expenses for 4 years and one return flight ticket to successful applicants.

Eligibility and applying

Applicants must:

  • Be Chinese students with a strong academic background.
  • Students must hold a PR Chinese passport.
  • Applicants can either be resident in China at the time of application or studying overseas. 
  • Students with prior experience of studying overseas (including in the UK) are eligible to apply. Chinese QMUL graduates/Masters’ students are therefore eligible for the scheme.

Please refer to the CSC website 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 (e.g. physics, mathematics, computer science, bioinformatics, or computational genomics). A masters degree is desirable, but not essential.

Applicants are required to provide evidence of their English language ability. Please see our English language requirements page for details.

The deadline for applications to Queen Mary is 30th January 2022. Applicants will need to complete an online application form by this date 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 CSC 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 CSC for the scholarship by the advertised deadline with the support of the project supervisor. For September 2022 entry, applicants must complete the CSC application on the CSC website between 10th March - 31st March 2022.

Only applicants who are successful in their application to CSC can be issued an unconditional offer and enrol on our PhD programme.

Apply Online


  • Bayesian molecular clock dating of species divergences in the genomics era. dos Reis M, Donoghue PCJ and Yang Z. (2016) Nature Reviews Genetics, 17: 71–80.
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