Research Fellow (Computer Science/Statistics/Electronics Engineering)

Nanyang Technological University; Singapore; On-site; SGD 78,000 - 123,000; Full time

Job summary

NTU Singapore's CCDS invites applications for a Research Fellow to advance probabilistic machine learning, causal discovery and GenAI. The role focuses on latent dynamic modelling and scalable architectures, with an emphasis on identifying latent systems from data.

The successful candidate will collaborate with a dynamic team, publish high-quality work, and contribute to joint projects with industry and academia in Singapore.

Qualifications

• PhD required in a relevant field (CS/Statistics/EE).
• Independent, analytical and proactive with team spirit.
• Strong verbal and written communication skills.
• In-depth domain knowledge related to AI/ML research.
• Proven ability to conduct innovative research.
• Capable of cross-disciplinary collaboration with industry/academia.
• Willingness to adapt and explore new ideas in AI research.

Responsibilities

• Conduct research in AI/ML, especially probabilistic ML and scalable sequence networks.
• Publish academic papers and patent applications.
• Contribute to annual report writing and presentations.
• Collaborate with faculty, staff and students on robotics and AI projects and supervise graduate students.
• Engage with industry or academic partners to explore opportunities and deliver project results.

Skills

Analytical thinker

Independent

Team player

Excellent communication

Collaborative mindset

Education

PhD in Computer Science or related field

Job description

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.

Dr Yingzhen Li (https://yingzhenli.net) and her research group at NTU are looking for a Research Fellow (RF) to carry out in research in probabilistic machine learning, causal discovery and GenAI, by exploring cutting-edge approaches such as causal representation learning, dynamical systems, sequence generative models and world modelling. Emphasis will be on methods that design and implement new architectures for latent dynamic modelling to enable identification of latent dynamical systems from observation data with both causal identification and statistical estimation guarantees. The role also involves exploration for emerging research directions, synthesizing technical ideas, and engaging with GenAI industry and open-source communities.

Job Responsibilities:

• Conduct the research in AI/ML domains, especially in probabilistic ML and scalable sequence network architectures
• Produce academic publications such as research papers and patent applications
• Contributing to annual report writing and presenting
• Collaborate with faculty, research staff, and students on joint robotics and AI projects and support the supervision of graduate students.
• Engage with industry or academic partners when required to explore collaborative opportunities and contribute to project deliverables.

Job Requirements:

• PhD degree in Computer Science, Statistics, Electronics Engineering or equivalent.
• Independent, highly analytical, proactive and a team player
• Excellent teamwork and verbal, written communication skills
• In-depth knowledge relevant to the project domain.
• Demonstrated capability to conduct innovative research.
• 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.
• Ability to design and implement new experimental methods.
• High-level expertise in the required experiment or modelling methods.
• Ability to initiate collaboration research in multidisciplinary team.
• Oversee and report project progress.
• Ability and willingness to work some flexible hours.

We regret that only shortlisted candidates will be notified.