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Design of experiments for network science


   Mathematics

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  Dr B Parker  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

The successful applicants will join the internationally recognised researchers in the Department of Mathematics. This exciting research project is focused on extending statistical theory, algorithms and tools to allow experimental design on a connected world.

Design of Experiments (DOE) is a statistical field that allows scientists to maximise information derived from experiments, making stronger conclusions and/or reducing the cost of doing science. This project applies DOE to Network Science and answers fundamental questions about how we measure and make conclusions when links between experiments are complex. It extends previous work by the supervisor.

Applicants will be required to demonstrate their ability to:

  • understand statistical theory of experimental design and develop it to particular experiments and applications on networks;
  • collaborate with statisticians and scientists and understand the challenges in different disciplines;
  • learn to work to develop algorithms with statistical software, such as R.

Students will ideally have some experience with networks and/or experimental design, although students with good statistical backgrounds without previous experience in this field are encouraged to apply.


Funding Notes

Brunel offers a number of funding options to research students that help cover the cost of their tuition fees, contribute to living expenses or both. See more information here: https://www.brunel.ac.uk/research/Research-degrees/Research-degree-funding. The UK Government is also offering Doctoral Student Loans for eligible students, and there is some funding available through the Research Councils. Many of our international students benefit from funding provided by their governments or employers. Brunel alumni enjoy tuition fee discounts of 15%.

How good is research at Brunel University London in Mathematical Sciences?


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

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