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Data analytics

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

In recent years, more and more data are available in many areas. We live in a very data-rich world. Our challenge is obtain information or to develop understanding from such data. There are applications in many areas like health, brain studies, retail sector, banking, social media, etc. For example, people can experience different emotions when listening to music. A growing number of studies have investigated the brain structures and neural connectivities associated with perceived emotions. However, very little is known about the effect of an explicit act of judgment on the neural processing of emotionally-valenced music. The aim of the project is to extract consistent information, which requires development of novel techniques and tools. The project will review existing techniques and develop new and improved ones.
This project will involve programming, signal processing, machine learning, mathematical analysis, and good writing ability for presentation of technical work. An ideal candidate will have a very good Master degree or a First Class Bachelor degree. Below are some publications from my group. These will give you good indications of the work we have done already and the developments of our ideas, techniques, and implementations.

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: View Website. Recently the UK Government made available the Doctoral Student Loans of up to £25,000 for UK and EU 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%.)


1. B Abu Jamous, R Fa, and A K Nandi, "Integrative Cluster Analysis in Bioinformatics", Published by John Wiley & Sons, Chichester, West Sussex, UK, 2015 (ISBN 978-1-118-90653-8).

2. C Liu, E Brattico, B Abu Jamous, C Pereira, T Jacobsen, and A K Nandi, “Effect of explicit evaluation on neural connectivity related to listening to unfamiliar music", Frontiers in Human Neuroscience, DOI: 10.3389/fnhum.2017.00611, vol. 11, (13 pages), 2017.

3. B Abu Jamous, F M Buffa, A L Harris, and A K Nandi, “In vitro downregulated hypoxia transcriptome is associated with poor prognosis in breast cancer", Molecular Cancer, DOI: 10.1186/s12943-017-0673-0, vol. 16, no. 105, (19 pages), 2017.

4. C Liu, B Abu Jamous, E Brattico, and A K Nandi, “Towards tunable consensus clustering for studying functional brain connectivity during affective processing", International Journal of Neural Systems, DOI: 10.1142/S0129065716500428, vol. 27, no. 2, 1650042 (16 pages), 2017.

5. B Abu Jamous, R Fa, D J Roberts, and A K Nandi, “Comprehensive analysis of forty yeast microarray datasets reveals a novel subset of genes (APha-RiB) consistently negatively associated with ribosome biogenesis", BMC Bioinformatics, DOI: 10.1186/1471-2105-15-322, vol. 15, no. 322, 2014.

6. V Alluri et al., "From Vivaldi to Beatles and back: predicting lateralized brain responses to music", NeuroImage, vol. 83, pp. 627-636, 2013.

How good is research at Brunel University London in General Engineering?

FTE Category A staff submitted: 63.45

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

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