Computer Science

The Department of Computer Science is always keen to attract high-quality PhD students.

SWANSEA SCIENCE DOCTORAL TRAINING CENTRE PHD SCHOLARSHIPS 2017/2018

Swansea Science DTC is a community committed to undertaking world-class research that has a positive impact globally.  

We have a number of fully-funded PhD scholarships for 2017/2018 entry.  These are competitively-funded scholarships from five of our subject areas: Biosciences, Computer Science, Geography, Mathematics and Physics.  Project descriptions can be found by clicking on the project titles below.

Closing date for applications:  30 April 2017

Potential PhD supervisors and research topics

Potential supervisor

Research topics

Dr Daniel Archambault

  • Visualization, information visualization (particularly dynamic data)
  • Social media and network visualization and some analysis
  • Perceptual issues in visualization
  • Graph drawing and network visualization
  • Interface design and HCI

Prof Arnold Beckmann

  • Logic, proof theory and proof complexity
  • Bounded arithmetic and propositional proof complexity 

Dr Ulrich Berger

  • Logic for computer science
  • Functional programming
  • Interactive theorem proving
  • Program verification
  • Program extraction
  • Semantics of programming languages

Dr Jens Blanck

  • Computability
  • Domain theory
  • Exact real arithmetic
  • Continuous data types
  • Topological spaces

Dr Rita Borgo

  • Scientific Visualization
  • Information Visualization
  • Human Factors in Visualization

Dr Parisa Eslambolchilar

  • Mobile HCI
  • Dynamic Continuous Interaction
  • Physical Activity
  • Mental health and well being
  • Sonification
  • Brain Computer Interaction
  • Ubiquitous Interaction
  • Tangible Interaction

Prof Matt Jones

  • HCI: special interest in mobile and ubiquitous systems
  • Context-based systems
  • Infrastructures and interactions for challenging environments

Dr Mark W Jones

  • Computer Graphics (global illumination)
  • Visualisation (particularly biological or sports data)
  • Volume visualisation
  • Information visualisation

Dr Oliver Kullmann

  • Satisfiability (SAT)
  • Algorithms
  • Complexity theory
  • Combinatorics
  • Data analysis
  • Philosophy

Dr Robert S Laramee

  • Data visualization
  • Data analysis
  • Information visualization
  • Scientific visualization
  • Computer graphics
  • Human factors

Dr Stephen Lindsay

  • Understanding attitudes towards Nanohealth
  • Designing around attitudes towards Nanohealth

Prof Faron G Moller

  • Concurrency theory
  • Modal and temporal logics
  • Formal verification

Dr Benjamin Mora

  • Ray-tracing
  • Global illumination
  • Image and volume representations
  • 3D displays
  • High Performance Computing

Dr Markus Roggenbach

  • Specification languages and their semantics
    (CSP, Timed-CSP, CASL)
  • Verification
  • Testing
  • Tool development
  • Knowledge transfer

Dr Monika Seisenberger

  • Extraction of programs from proofs
  • Modelling, specification, and verification
  • Verification of railway control systems
  • Interactive theorem proving
  • Logic and proof theory
  • Formal methods in security and cyberterrorism

Dr Anton Setzer

  • Proof theory
  • Type theory
  • Constructive mathematics
  • Interactive theorem proving
  • Agda
  • Programming with dependent types
  • Verification of critical systems
  • Verification of railway interlocking systems

Dr Gary Tam

  • Data visualization
  • Geometry processing
  • Computer vision
  • Pattern matching

Prof Harold W Thimbleby

  • Safe design, particularly user interfaces in healthcare
  • Human-computer interaction, particularly in healthcare
  • Human error and computers
  • The public understanding of science

Prof John V Tucker

  • Theory of programming and specification
  • Physical foundations of computation
  • History of computing
  • Technical, social, and cultural aspects of technological development
  • History of science in Wales

Dr Xianghua Xie

  • Computer vision
  • Image processing
  • Medical imaging
  • Pattern recognition
  • Big data and machine learning