Research Fellow – AI, Machine Learning & Robotics

About the role

The School of Electrical and Electronic Engineering at Nanyang Technological University is seeking a Research Fellow to advance accelerated AI, machine learning and robotics algorithms. The role focuses on improving computational efficiency, reducing memory usage and enabling energy‑aware deployment of foundation models across cloud, edge and robotic platforms.

Key responsibilities

• Develop AI/ML and robotics algorithms that lower computation cost, memory footprint and power consumption.
• Design and optimise training and inference pipelines for large language models, vision‑language models and vision‑language‑action models of varying scales.
• Apply and extend model‑compression techniques such as quantisation, pruning, knowledge distillation and low‑rank adaptation.
• Conduct algorithm‑hardware co‑design for efficient deployment on edge, robotic and heterogeneous computing platforms.
• Implement, evaluate and benchmark accelerated models under latency, throughput and energy constraints.
• Publish research findings in top‑tier conferences and journals and contribute to open‑source codebases.
• Supervise and mentor PhD students, research assistants and master’s students.
• Collaborate with interdisciplinary teams spanning AI, systems and robotics.

Required profile

• Completed PhD in Computer Science, Electrical Engineering, Robotics, Artificial Intelligence or a closely related discipline.
• Strong research background in AI and machine learning with a focus on efficiency‑oriented methods.
• Experience in developing and evaluating algorithms for large‑scale foundation models.
• Proven record of publishing in reputable AI, ML or robotics venues.

Required skills

• AI and machine learning algorithm development
• Robotics algorithm design
• Model compression (quantisation, pruning, knowledge distillation, low‑rank adaptation)
• Algorithm‑hardware co‑design
• Efficient training and inference pipelines for foundation models
• Cloud, edge and heterogeneous platform deployment