Research Fellow (Computer Engineering/Computer Science/Applied Mathematics)

Visa Hunt; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

NTU Singapore in Singapore is seeking a highly capable researcher for the College of Computing and Data Science to advance AI-for-Science initiatives. You will conduct research, prototype workflows, collaborate with AI researchers, and contribute to high-impact publications.

The role emphasizes strong analytical skills, independence, and teamwork in a fast-paced, interdisciplinary environment. Applicants should hold a PhD in a relevant field and demonstrate expertise in ML optimization, Python,

Qualifications

• PhD in Computer Engineering, Computer Science, Applied Mathematics, or equivalent.
• Strong academic background in machine learning and convex optimization.
• Prior experience in software development in machine learning systems is highly desirable.
• Proficient in Python and ML frameworks such as PyTorch.
• 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.

Responsibilities

• Conduct research on the design and analysis of efficient AI-for-Science systems, leveraging foundation models (including small language models) and parameter‑efficient adaptation techniques such as LoRA, grounded in a strong understanding of optimization methods and deep learning to enable scientific reasoning.
• Develop software prototypes for automated research workflows that integrate autonomous discovery pipelines with modern deep learning architectures, while addressing real‑world data constraints such as privacy and heterogeneity.
• Collaborate with AI researchers on translational applications to validate and refine our AI-for-Science methodologies in impactful settings.
• Publish in top‑tier conferences and journals (e.g., NeurIPS, ICML, ACL, ACM KDD, IEEE TKDE).
• Support the supervision of graduate students and actively contribute to the research group’s collaborative and interdisciplinary activities.

Skills

Analytical thinking

Independent

Team player

Excellent communication

Education

PhD in Computer Engineering, Computer Science, Applied Mathematics or equivalent

Tools

Python

PyTorch

ML frameworks

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.

Key Responsibilities:

• Conduct research on the design and analysis of efficient AI-for-Science systems, leveraging foundation models (including small language models) and parameter‑efficient adaptation techniques such as LoRA, grounded in a strong understanding of optimization methods and deep learning to enable scientific reasoning.

• Develop software prototypes for automated research workflows that integrate autonomous discovery pipelines with modern deep learning architectures, while addressing real‑world data constraints such as privacy and heterogeneity.

• Collaborate with AI researchers on translational applications to validate and refine our AI-for-Science methodologies in impactful settings.

• Publish in top‑tier conferences and journals (e.g., NeurIPS, ICML, ACL, ACM KDD, IEEE TKDE).

• Support the supervision of graduate students and actively contribute to the research group’s collaborative and interdisciplinary activities.

Job Requirements:

• Preferably PhD degree in Computer Engineering, Computer Science, Applied Mathematics or equivalent.

• Strong academic background in machine learning and convex optimization.

• Prior experience in software development in machine learning systems is highly desirable.

• Proficient in Python and ML frameworks such as PyTorch.

• 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.