The Baby-LINC Singapore Lab (https://blogs.ntu.edu.sg/baby-linc/) is looking for a talented Research Engineer I to join 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 Engineer I 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

• Lead the computational programming and algorithm development for personalized socially-augmented digital avatars, working closely with Prof Nadia Thalmann (a social robotics expert) on the design and customization of the avatars.

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

• Contribute toward 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, computational modelling.

• Help to oversee affiliated research students

Job Requirements

• Bachelor’s Degree in Computer Science, Engineering (including Biomedical Engineering), or related Technical and Computational fields

• Strong technical and programming skills, particularly in digital media and/or social robotics, as demonstrated by relevant research publications or other outputs

• Experience with computational modelling and advanced statistical analysis is preferred

• Experience with human psychological data collection and study design is preferred

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