Research Associate (NIE-SoLEC)

NANYANG TECHNOLOGICAL UNIVERSITY; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

Nanyang Technological University is seeking a Research Associate for a 12-month contract at the Science of Learning in Education Centre. This role involves developing a visual analytics system to analyze student emotions from classroom videos, utilizing machine learning techniques and strong programming skills to enhance educational insights.

Qualifications

• Experience with video data visualization preferred.
• Strong research background in emotion recognition using videos.
• Ability to work independently with minimum supervision.

Responsibilities

• Conduct literature reviews related to the project.
• Manage data and perform data analysis.
• Supervise students and manage project aspects.

Skills

Data Visualization

Machine Learning

Deep Learning

Emotion Recognition

Communication

Education

Master’s Degree in Computer Science or related field

PhD in relevant field (if applicable)

Tools

Python

C/C++

MATLAB

Job description

The National Institute of Education invites suitable applications for the position of Research Associate on a 12-month contract at the Science of Learning in Education Centre, with possible extension.

Project Title: EmoRoom: A visual analytics system unveiling student’s emotions from classroom video data

Project Introduction: We are seeking a highly motivated and skilled Research Associate to join our interdisciplinary team working on a cutting-edge research project titled "EmoRoom: A visual analytics system unveiling students’ emotions from classroom video data." The project aims to develop EmoRoom (Emotion + Classroom), an interactive visual analytics system to analyze and summarize student emotions from classroom videos, using emotion recognition algorithms and intuitive visualizations of data output. This development reflects broader efforts regarding the creation of an intuitive graphical user interface for use by education stakeholders without programming backgrounds (e.g., practitioners), and is expected to help research learning emotions and guide teacher professional development in the area of Social-Emotional Learning.

Job Requirements

• A Master’s Degree in computer science, machine learning, artificial intelligence, or a related field. Candidates with a PhD may be considered for a Research Fellow position instead.
• Prior experience with video data visualization research will be a plus
• Prior experience in data visualization techniques, machine/deep learning algorithms is preferable.
• Proficient with programming in Python, C/C++ and/or MATLAB.
• Strong research experience/track record in emotion recognition using videos will be a plus.
• Good written and verbal communication skills with evidence of proven writing skills from research papers or research reports.
• Able to work independently (with minimum supervision) to analyze data and communicate findings.
• Prior experience with the academic publication process.

Key Responsibilities

• Conducting comprehensive literature reviews on topics related to project.
• Manage data and perform data analysis under the supervision of the PI and Co-PIs.
• Disseminate the outcome of research in peer-reviewed publications of international standing.
• Propose novel ideas in response to the latest research trends in the field of video data analysis.
• Perform research-related administrative work, e.g., purchase of equipment for research, and contribute to SoLEC
• Supervise students (i.e., URECA, FYP, etc.)
• Management of multiple aspects of the research project, including project management, liaising with stakeholders, and data analysis.
• Other duties as assigned by PI and Co-PIs

Application

Applicants (external and internal) will apply via Workday. We regret that only shortlisted candidates will be notified.

Workday Job Requisition: R00020945

(https://ntu.wd3.myworkdayjobs.com/Careers/job/NTU-Main-Campus-Singapore/Research-Associate--Science-of-Learning-in-Education-Centre---NIE-_R00020945)

Closing Date

Closing date for advertisements will be set to 14 calendar days from date of posting.