Artificial Intelligence Machine Learning and Advanced Computing PhD


Course facts

  • Name: Artificial Intelligence Machine Learning and Advanced Computing
  • Qualification: PhD
  • Duration: 4 years

Two fully-funded 4-year PhD scholarships are available to start in October 2019 in the area of Artificial Intelligence machine learning and advanced computing. The PhDs are suitable for graduates with a keen interest in AI algorithms for data analytics, visualisation and image analysis. 

The 4-year PhD scholarships, will sit within the UKRI Centre for Doctoral Training in Artificial Intelligence, Machine Learning & Advanced Computing (CDT-AIMLAC). The two students will be based at Bangor University, located within the School of Computer Science and Electronic Engineering. Funding will cover the full cost of UK/EU tuition fees and an annual stipend of £14,750. Additional funding is available for research expenses.

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Candidates must identify their preference of primary supervisor and project from:

  • T1: Classification of Wide Data and Weakly Supervised Data (Prof. Lucy Kuncheva) focusing on wide data sets (with small sample size and large dimensionality) using weak supervision, semi supervised learning and restricted set classification.
  • T2: Artificial Intelligence for Immersive Analytics (IA) (Dr Panos Ritsos) concerned with the design, development, application and evaluation of AI-driven mechanisms and models for context-aware, context-adaptive and predictive interfaces for immersive analytics using Virtual Reality or Mixed Reality.
  • T3: A grammatical approach to neuroevolution (Dr Bill Teahan), focusing on evolutionary algorithms to generate some form of artificial neural network using context-free grammars to constrain the search space for genetic programming.
  • T4: Smart storytelling for scientific data visualisation (Prof. Jonathan C. Roberts); this research will focus on automatic design and layout of scientific visualisations results using machine learning. Learning algorithms, metrics and methods will be researched to develop (semi-) automated data-storytelling.
  • T5: Interactive evolutionary learning for image analysis. (Dr Franck Vidal). The research will focus on the integration of evolutionary learning with interactive visualisation for semi-automated image analysis. 

The successful candidates will be required to attend taught components in year 1 including (foundations of AI, research methods), residential meetings, deliver responsible innovation, and engage with placements with external partners throughout the four-year programme. Placements may be six-month, or shorter three-month or two week blocks. Successful applicants will be registered at Bangor University throughout their period of study although the delivery of the related training in the PhD programme will be shared between the Universities of Aberystwyth, Bangor, Bristol, Cardiff and Swansea. 

The deadline for applications is 30 April 2019; however applications will be accepted until all positions are filled.

Course content is for guidance purposes only and may be subject to change.

Entry Requirements

Applicants should have at least a 2:1 degree in computer science, mathematics or electronic engineering (with substantial programming), or closely related discipline. You must have excellent programming skills and interest in AI, machine learning and advanced computing and one of the topics, above. You should have an aptitude and ability in computational thinking and methods (as evidenced by your degree).

We welcome applications by UK/Home and EU nationals. To qualify as a UK/Home applicant, prospective students must have been ordinarily resident in the UK for three years immediately prior to the start of the award, with no restrictions on how long they can remain in the UK. Residence in the UK that is solely for the purpose of education will only count towards these three years if the candidate is an EU national. 

More information on this exciting research can be found here.


To apply your application must include the following attachments in pdf form: 

  1. CV
  2. Degree certificates and transcripts (if you are still an undergraduate, provide a transcript of results known to date)
  3. A statement no longer than 1000 words that explains why you want to join our Centre, and your preferred topic/supervisor. 
  4. Academic references - all scholarship applications require two supporting references to be submitted. Please ensure that your chosen referees are aware of the funding deadline (to be determined), as their references form a vital part of the evaluation process. Please include these with your scholarship application.

The deadline for applications is 30 April 2019; however applications will be accepted until all positions are filled.

Further information

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