Research Associate (Computer Science)

Young and research-intensive, Nanyang Technological University, Singapore (NTU Singapore) is ranked among the world’s top universities. NTU’s College of Computing and Data Science (CCDS) is a leading college that is known for its excellent curriculum, outstanding and impactful research, and world-renowned faculty.

A hot bed of cutting-edge technology and groundbreaking research, the College aims to groom the next generation of leaders, thinkers, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and grow’. We welcome you to join our community of faculty, students and alumni who are shaping the future of AI, Data Science and Computing.

Job Responsibilities:  

• The Research Associate will support research on large language models (LLMs) and their applications in education.

• The project focuses on developing AI-based methods for automatic essay grading, meaningful feedback generation, and the transformation of abstract lecture slides into concrete explanatory content.

• The role involves designing and evaluating LLM-based algorithms, preparing and analysing educational datasets, developing prototype systems, and assessing the accuracy, reliability, and fairness of the generated grading and feedback.

• The Research Associate will work closely with the project team, contribute to research publications, and support the integration of the developed methods into educational technology platforms.

Job Requirements:

• Minimally Master degree in Computer Science

• Independent, highly analytical, proactive and a team player

• Excellent teamwork and verbal, written communication skills

• In-depth knowledge relevant to the project domain. Related background in GenAI with specific experience in working with large language models.

• The ability and willingness to adapt and incorporate novel ideas and approaches in scientific industry.

• Demonstrated ability to formulate hypothesis and design effective experimental plans.

• High-level expertise in the required experiment or modelling methods.

• Ability and willingness to work some flexible hours.

We regret that only shortlisted candidates will be notified.