Research course

Intelligent Modelling and Analysis

University of Nottingham · School of Computer Science

Entry requirements

2:1 (or international equivalent) in computer science or other relevant area.

Months of entry


Course content

Postgraduate study for the degree of PhD is offered in the Intelligent Modelling and Analysis (IMA) Research Group in computer science. The degree of MPhil (by thesis) is also available. Postgraduates without sufficient training in computer science at first-degree level may be required to attend appropriate taught modules.

IMA has established itself as a unique brand in the UK for end-to-end data modelling and analysis. We are a highly inter-disciplinary research group focusing on the development of models and techniques for
real-world and multifaceted problems in data analysis.

We encompass researchers from a variety of backgrounds including computer science, the biomedical sciences, operational research, mathematics, statistics and complexity science. The group currently has seven permanent academics, one support staff, ten research staff and over 40 Marie Curie Fellows and PhD students. We hold over £33m in current external research funding and have led a further £6m of completed projects.

The IMA group undertakes research into intelligent modelling and data analysis techniques to enable deeper and clearer understanding of complex physical and physiological problems. A particular strength of the group lies in the biomedical and security fields where extremely large data volumes have to be analysed in (near) real-time to very high levels of accuracy.

Typical techniques used by the IMA group include: artificial intelligence based data mining, artificial immune systems, computational modelling, discrete and agent-based simulation, fuzzy methodologies, image analysis and multi-sensor data fusion.

IMA's main research objectives are to:

  • conduct inter-disciplinary research to investigate novel and adventurous real-world problems;
  • focus on modelling, representation and transformation techniques to enable better decisions;
  • support the integration of emerging methodologies with more traditional approaches;
  • explore the applicability of complexity science to real-world challenges.

Qualification, course duration and attendance options

  • PhD
    full time
    36 months
    • Campus-based learningis available for this qualification
    part time
    72 months
    • Campus-based learningis available for this qualification

Course contact details

Postgraduate Enquiries
+44 (0)115 951 5559