Research Fellow, Computational Modelling

06 Nov 2020
End of advertisement period
06 Dec 2020
Contract Type
Full Time

The Centre for Lifelong Learning and Individualised Cognition (CLIC), funded by the National Research Foundation (NRF) in Singapore and coordinated through the Cambridge Centre for Advanced Research and Education in Singapore (CARES), is a collaboration between Nanyang Technological University (NTU) and the University of Cambridge. CLIC is a flagship programme in the Science of Learning to harness advancements in neuroscience to develop cognitive training programmes for the improvement of lifelong flexible learning, focusing initially on adolescents and young adults, but also envisaging work with infants and older adults.  This is a strategic global initiative for the Universities of Cambridge and NTU that brings together multidisciplinary expertise from over 30 investigators in the areas of Neuroscience, Psychology, Linguistics and Education across the two universities.

The CLIC program is seeking one full-time Research Fellow to oversee the statistical design and analysis pipeline of the main study. We anticipate that you will be a statistician, psychometrician, computational psychologist, or computational modeller with expertise in structural equation modelling (SEM) and Bayesian/frequentist approaches to data analysis. You will be a high-performing individual with a track-record of publication in areas such as (but not limited to) statistical modelling of neural or cognitive data, SEM, Bayesian methods, etc. You will primarily be supervised by Prof Zoe Kourtzi and Asst Prof Victoria Leong. You will also interact widely with other members of the academic consortium.

Given the highly inter-disciplinary nature of the project, the Research Fellow can also expect to be offered opportunities for involvement in research activities related to human neuroimaging, infant cognition/learning and pedagogy.

The responsibilities of the position include:

  • Overseeing the overall statistical design and data analysis pipeline of the programme, integrating multiple domains and forms of data (behavioural, neural, demographic, etc)
  • Conducting statistical modelling and analysis of data using SEM and Bayesian/frequentist approaches
  • Supervising junior members of the research team
  • Leading the authorship of academic publications
  • Contributing to the production of research reports for funders and the public
  • Contributing to the dissemination of research findings
  • Performing other research-relevant tasks as required by the Principal Investigators

Essential requirements:

  • Doctorate (PhD) degree in specializing in either in statistics, psychometrics, computational modelling, experimental psychology, cognitive psychology, neuropsychology, electrical engineering, medical engineering, computer science, or related fields
  • Expertise in psychometrics and statistical modelling, specifically SEM and Bayesian statistical approaches
  • A publication track record and other evidence of research productivity
  • Experience working with human experimental data in neuropsychology or cognitive psychology
  • Strong interpersonal, written and verbal communication skills
  • Excellent organizational skills and the ability to work within given deadlines

Preferred requirements:

  • Experience working on large-scale studies and in the analysis of complex datasets
  • Experience with neuroimaging techniques (MRI, EEG or TMS)
  • Familiarity with image data analysis tools such as SPM, FSL, AFNI, DSIStudio, Python etc
  • Data management experience with REDCap
  • Experience in a supervisory context

We regret that only shortlisted candidates will be notified.

Hiring Institution: NTU

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