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Postdoctoral Research Fellow in Education and Data Science
Whiteknights Reading UK

Job reference: SRF27881

Location: Whiteknights Reading UK

Closing date: 28/02/2019

Job live date: 28/01/2019

Salary: £30,395 - £33,199 per annum

Employment type: AR-Research

Department: School of Psychology & Clinical Language Sciences

Division: Not specified

Hours Per Week:: 1.0 FTE

Employment Basis/Type: Full-Time, Fixed Term

We are seeking a postdoctoral research fellow to undertake research in the Motivation Science Lab (PI: Kou Murayama; at the University of Reading in education and data science, specifically to examine the function of interest and curiosity in education using publicly-available data.

The successful candidate will be part of a big interdisciplinary team funded by the prestigious Leverhulme Research Leadership Award --- a 5-year £1M award. We aim to establish an integrative theory of human interest and its relations to extrinsic rewards, combining psychological, neural, computational, and applied perspectives.

The postdoctoral research fellow will work on a project that applies multivariate statistical analysis and/or machine learning to examine the role of interest and curiosity in education, with additional possibility to work on an educational intervention study.

The position will be for 2.5 years (full-time) and the expected start date is on May 1st, 2019 (negotiable).

The School of Psychology and Clinical Language Sciences at the University of Reading was ranked in the top 20 (15th) in the UK in its unit of assessment in the 2014 Research Excellence Framework based on research power. The university provides cutting-edge computational facilities to conduct a variety of advanced statistical analysis and statistical simulation.

You will need to have:

  • PhD in Psychology, Education, Applied Statistics, or other related discipline (or working towards completion)
  • Good knowledge about education science in general (ideally good knowledge on motivation research in education)
  • Good data analysis skills (multivariate statistical analysis, longitudinal data analysis, machine learning, etc.): Please specify the type of analysis and program that you can use.
  • Evidence of having published peer-reviewed papers on the relevant topics
  • Ability to work independently, good organizational skills, and good interpersonal skills.

Interview date: 15/03/2019

Informal contact details

Contact role:

Line Manager (PI)

Contact name:

Kou Murayama

Contact phone:

0118 378 5558

Contact email:

The University is committed to having a diverse and inclusive workforce, is a Stonewall Diversity and Global Diversity Champion, and supports the principles of the Race Equality Charter and Athena SWAN.  Applications for job-share, part-time and flexible working arrangements are welcomed and will be considered in line with business needs.


The closing date for this job has now passed.


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