Postgraduate Research Opportunity

Enhancing cognitive fitness and attention for active mathematical learning through neural engineering


Title: SCH05: Enhancing cognitive fitness and attention for active mathematical learning through neural engineering

Funding: Full time Home/EU fees and a stipend of £15,009 p.a. (terms & conditions)

Application deadline: 7 May 2019

Start date: October 2019

Duration: 3 years (full time)

Location: Colchester Campus

Based in: School of Computer Science and Electronic Engineering (in collaboration with the Department of Psychology, and the Department of Mathematical Sciences)


Brain health and performance both matter. Attempts to develop effective ‘brain training’ technology has not been very successful yet due to lack of neuroscientific evidence.

This studentship will research and develop a new neuro-adaptive learning environment for mathematical education. The information technology (IT)-based learning environment will adapt the learning content based on the learner’s task performance and brain signals (electroencephalogram (EEG)).

Brain signals provide information about the learner’s mental state such as for example the level of motivation or the perceived task difficulty. Combination and processing of data from both overt and covert behaviour allows continuous adjustment of learning environment and learning material to optimize learning success (for example, increase difficulty to challenge the player). 

You will conceptualize, design and implement the mathematical learning environment, adapt and develop new signal processing methods for robust estimation of motivation/task difficulty from EEG, conduct an evaluation study, and investigate what factors result in the improvement of the learner’s skill.


The award consists of a full Home/EU fee waiver or equivalent fee discount for overseas students (further fee details), a doctoral stipend equivalent to the Research Councils UK National Minimum Doctoral Stipend (£15,009 in 2019-20), plus £2,500 training bursary via Proficio funding, which may be used to cover the cost of advanced skills training including conference attendance and travel.


Dr Ian Daly


School of Computer Science and Electronic Engineering, University of Essex

Dr Ian Daly is a lecturer in Brain-Computer Interfaces and a member of the Brain-Computer Interfacing and Neural Engineering research group. His research interests include BCI, Assistive Technology, Machine learning, and Signal processing. He is also interested in semantic encoding, neurophysiological correlates of motor control, emotion, and stimuli perception and how they differ between healthy individuals and individuals with neurological and physiological impairments.

Dr Helge Gillmeister


Department of Psychology, University of Essex

Dr Helge Gillmeister is an expert in EEG methods for Cognitive Neuroscience, with a background in Psychology, Cognitive Science and Cognitive Neuroscience. She is interested in how bodily signals give rise to the sense of self, and how signal processing and machine learning techniques can be applied to map the interactions between attitudinal factors (e.g. maths anxiety) and brain activity in response to relevant triggers (e.g. maths puzzles).

Dr Alexei Vernitski


Department of Mathematical Sciences, University of Essex

Dr Alexei Vernitski conducts research in mathematical education, concentrating on how to increase learners’ motivation and reduce learners’ anxiety. His approach to teaching mathematics is based mainly on principles formulated by Jo Boaler and known as “Mathematical Mindsets”.


Essential skills of the successful candidate

Computer programming. This may include the following skills (or equivalent to them):

  • Unity
  • Python
  • Web development
  • Matlab for data processing

Desirable skills

Experience of conducting EEG experiments and cleaning up and processing EEG data

Some knowledge of cognitive psychology

Experience with programming computer games, including computer puzzles

An interest in teaching mathematics

How to apply

You can apply for this postgraduate research opportunity online.

Please upload with your application a CV, a covering letter, a personal statement and transcripts of any undergraduate or masters programmes.

In addition to these documents, we would like the applicant to provide

  • Examples of their recent code development, for example, screenshots or links to GitHub.
  • A short description of how they would test if a game like Lumosity is benefiting the player’s cognitive fitness

Instruction to applicants

When you apply online you will be prompted to fill out several boxes in the form:

  • For "Course title" please put "PhD Computer Science"
  • For "Proposed research topic or area of research" please put the title of this studentship (SCH05: Enhancing cognitive fitness and attention for active mathematical learning through neural engineering)
  • For "If you have contacted a potential supervisor..." please put the name of the lead supervisor (Professor Reinhold Scherer)

If you have any informal queries about this opportunity please email the lead supervisor, Professor Reinhold Scherer (

You can find the terms and conditions of this studentship here (PDF).