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Modelling stochastic processes in human population genetics

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Competition Funded PhD Project (Students Worldwide)
    Competition Funded PhD Project (Students Worldwide)

Project Description

The School of Mathematical Sciences of Queen Mary University of London invite applications for a PhD project commencing either in September 2020 for students seeking funding, or in January 2020 or April 2020 for self-funded students. The deadline for funded applications is the 31st of January 2020. The deadline for China Scholarship Council Scheme applications is 12th January 2020.

This project is supervised by Dr. Weini Huang.

Many diseases in human are caused by genetic alternations and errors starting from a single cell. The origin of these genetic errors and the expansion of the abnormal cells carrying these genetic errors are often stochastic processes.
There is an urgent need to understand the difference between health and non-health tissues such as tumours, in order to explain the mechanisms of disease development and even predict the possible dynamics in such stochastic systems.

The aim of this PhD project is to use stochastic models based on simple mechanistic assumptions to explain observed patterns in human cells, including healthy tissues and tumours. Analytical work will involve to use, for example, probabilistic and Markov models to calculate the expected frequency distributions of these genetic errors in a population of human cells. We will also use Gillespie simulations and Bayesian statistics to compare the mechanistic models with measured genetic patterns, e.g. extra-chromosol DNA distributions in single cells and mitochondrial DNA data in normal liver tissues. These will be done in cooperation with different research groups in the Barts Cancer Institute in the School of Medicine and Dentistry in Queen Mary University of London.

In general, we aim to build general stochastic models and analysis to understand and quantify the growth history of human tissues by using experimental and clinical data of genetic information. The candidate should hold a BSc, MSc or an equivalent degree in applied mathematics, physics, or computer science.

The application procedure is described on the School website. For further inquiries please contact Dr Weini Huang at . This project is eligible for full funding, including support for 3.5 years’ study, additional funds for conference and research visits and funding for relevant IT needs. Applicants interested in the full funding will have to participate in a highly competitive selection process.

Funding Notes

This project is eligible for full funding, including support for 3.5 years’ study, additional funds for conference and research visits and funding for relevant IT needs.

This project can be undertaken as a self-funded project. Self-funded applications are accepted year-round for a January, April or September start.

We welcome applicants through the China Scholarship Council Scheme (deadline for applications 12th January 2020).

The School of Mathematical Sciences is committed to the equality of opportunities and to advancing women’s careers. As holders of a Bronze Athena SWAN award we offer family friendly benefits and support part-time study.

References

https://elifesciences.org/articles/08687.pdf

https://www.nature.com/ng/journal/v48/n3/abs/ng.3489.html

Related Subjects

How good is research at Queen Mary University of London in Mathematical Sciences?

FTE Category A staff submitted: 34.80

Research output data provided by the Research Excellence Framework (REF)

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