Computer Science (CDT) PhD
Warning: DOMDocument::loadXML(): Empty string supplied as input in /afs/mcc/common/WWW/DocumentRoots/6/epscl/dev/comp_sci/legacy/php/coursemarketing/_course_functions_t4.php on line 189
Warning: DOMDocument::loadXML(): Start tag expected, '<' not found in Entity, line: 2 in /afs/mcc/common/WWW/DocumentRoots/6/epscl/dev/comp_sci/legacy/php/coursemarketing/_course_functions_t4.php on line 105
A new approach
The Manchester Centre for Doctoral Training in Computer Science proposes a model of PhD training which combines the deep technical research study associated with the UK PhD with training and practical experience in creativity and innovation and scientific evaluation, and gives students experiences practicing their research skills by working with users from outside academia.
The CDT in Computer Science is led by Professor Steve Furber and Dr. Jonathan Shapiro.
We are now open for September 2017 applications.
All UK/EU applicants to the CDT are considered for this funding as part of the application process.
The School of Computer Science’s research brings together an understanding of foundations, technologies and applications. We have research groups operating across the spectrum. Few universities in the world are able to offer the same breadth of expertise. Research areas within the school include:
- Advanced Interfaces
- Advanced Processor Technologies
- Bio-Health Informatics
- Formal Methods
- Imaging Sciences
- Information Management
- Machine Learning and Optimisation
- Nano Engineering and Storage Technologies
- Software Systems
- Text Mining
About the Programme
The UK three-year PhD by necessity of its length focuses on excellence in research, and understanding the academic literature. This focus is very important and will not be lost in the 4-year approach of the CDT. However, students will also gain training and experience in all of the research steps: creativity and innovation, thinking about impacts of research at the outset, and understanding through collaboration with industrial and outside users how research can have big impacts in non-academic ways. We also give the students a broader range of experiences in research problem-solving, which will produce much better prepared post-graduates.
The programme consists of an initial ‘foundation period’ of six months of taught components, followed by a 3.5 year period of focused PhD level research, carried out under the supervision of a PhD supervisor or team of supervisors.
The programme uses two integrative themes to focus students on the challenges facing the next generation of researchers in computer science rather than particular methods associated with a research community. These two themes cut across computer science and represent broad areas in which Manchester has a large and world-leading research base:
- Engineering for large and complex data - how to deal with the increasing explosion of data and build models of complex systems. How to use these to extract knowledge, fuse with existing knowledge, and make predictions.
- Engineering for new technologies - how to optimise the effective and energy-efficient use of multicore processors and interconnected embedded "smart" devices; explore new uses for smart personalised devices, dealing with security issues and other risks.
Manchester is adopting a new and unique approach to PhD training that looks to achieve the following goals:
- Give students deeper formal training in their technical field.
- Provide explicit training in creativity and innovation.
- Provide explicit training in scientific evaluation and experimental methods.
- Make students aware of research impact at an early stage of research, by teaching them to produce an impact survey and by having them carry out studies of impacts of research.
- Give students experience working in groups on real problems in collaboration with end users.
- Give students opportunities to work in academic and industry research labs.
- Use integrative themes to get students thinking across the discipline.
- Provide students with sufficient experience and practice in different research areas to allow them to make an informed choice of research topic.