Research Fellow – Deep Learning & Optimization

About the role

NTU’s College of Computing and Data Science is seeking a Research Fellow to conduct independent research in deep learning, large‑scale model optimisation, and generalisation. The role involves collaborating with academic and industrial partners while mentoring students.

Key responsibilities

• Conduct independent research on deep learning, large‑scale model optimisation, and generalisation.
• Explore scalable optimisation methods for large‑scale, distributed, and multi‑node collaborative training.
• Perform theoretical analysis of optimisation and generalisation to guide practical algorithm design.
• Publish high‑quality papers in top‑tier machine learning conferences and journals.
• Provide guidance and assistance to students involved in the project.
• Collaborate with academic and industrial partners and undertake related research duties.

Required profile

• PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Strong theoretical research capability, especially in optimisation, convergence, stability, or generalisation of deep learning models.
• Experience with machine‑learning optimisation, preferably in distributed or multi‑node collaborative training and large‑scale training.
• Demonstrated record of publications in top‑tier conferences/journals such as ICML, ICLR, NeurIPS, or IEEE TPAMI.
• Ability to formulate fundamental research problems, develop novel optimisation methodologies, and conduct rigorous theoretical and empirical studies.
• Independent, highly analytical, proactive, and effective in a collaborative research environment.