The Baby-LINC Singapore Lab (https://blogs.ntu.edu.sg/baby-linc/) is looking for a talented Research Fellow to support the leadership of a new research study funded by a Ministry of Education Social Sciences and Humanities Research (SSHR) Fellowship to A/Prof Victoria Leong on “The digital future of human learning: Social optimisation of digital media for early learning”. This project aims to develop socially-intelligent digital technology to support interactive learning in infants and young children, using dyadic-EEG techniques to monitor brain learning states during social interaction (see Leong et al, 2017 PNAS; Wass et al, 2020 TICS). The Research Fellow will join a dynamic and friendly international research team which operates in Singapore and in Cambridge (UK), although the data collection for this study will be conducted entirely in Singapore.

Key Responsibilities

• Assist the Principal Investigator (PI) with day-to-day management of the SSHR project, working in close coordination with the other staff and students on the team.

• Lead data collection efforts for the main experimental studies involving over 100 parent-infant dyads.

• Lead data analysis and research publication in one or more of these core domains: dyadic EEG+ECG, eye-tracking, motion tracking, speech analysis, social interaction analysis, digital media programming, computational modelling.

• Provide strong administrative oversight to ensure timely scientific and financial reporting to the funder, compliance with data protection and ethical regulations, etc.

• Provide pro-active and effective trouble-shooting for any problems that arise

• Supervise research students.

Job Requirements

• A PhD in Psychology, Neuroscience, Biomedical Engineering, Medical Sciences or related Technical and Computational fields

• Strong technical and analytical skills, as demonstrated in relevant research publications

• Experience with human psychological data collection and study design

• Experience in project management and research administration is preferred

• Experience in working with children (particularly infants) and families is preferred

• Experience with EEG and other forms of neuroimaging data collection and analysis is preferred

• Experience with computational modelling and advanced statistical analysis is preferred

• Experience with measurement and analysis of human social interactions is preferred

• Experience with digital media programming is preferred

• Efficient, organised and self-motivated with the ability to work to tight deadlines

• A good team player with strong interpersonal and communication skills.

We regret that only shortlisted candidates will be notified.