AI/ML & Robotics Research Assistant - Efficient Models

NANYANG TECHNOLOGICAL UNIVERSITY; Singapore; On-site; SGD 52,000 - 70,000; Full time

Job summary

Nanyang Technological University’s School of Electrical and Electronic Engineering invites applications for a Research Assistant (PhD student) to develop accelerated AI, machine learning, and robotics algorithms focusing on efficiency, memory reduction, and energy-aware deployment.

The role targets foundation models (LLMs, VLMs, VLAs) across scales and settings, advancing efficient AI for cloud, edge, and robotic platforms.

Qualifications

• Bachelor's degree in CS/EE/Robotics or closely related field.
• Strong research background in AI/ML with a focus on efficient or accelerated models.
• Experience with model compression techniques (quantization, pruning, distillation, LRA).
• Experience with foundation models (VLMs/LLMs/VLAs) is a strong advantage.
• Solid understanding of algorithm-hardware co-design for robotics or edge AI.
• Strong programming skills in C, C++, Python; DL frameworks such as PyTorch or TensorFlow.
• Familiarity deployment constraints on cloud/edge/embedded systems.
• Experience in robotics or embodied AI is an advantage.
• Strong publication record or potential to publish in leading venues.

Responsibilities

• Develop accelerated AI/ML and robotics algorithms that reduce computation, memory, and power.
• Design and optimize training and inference pipelines for foundation models across sizes and deployments.
• Apply model compression techniques including quantization, pruning, distillation and LRA.
• Conduct algorithm-hardware co-design for efficient deployment on robotic and edge platforms.
• Develop deployment methods for AI models on cloud and edge devices with latency focus.
• Implement, evaluate, and benchmark accelerated models with rigorous tests.

Skills

C/C++

Python

PyTorch

TensorFlow

Education

Bachelor's degree in Computer Science / Electrical Engineering / Robotics

Tools

Git

CUDA

Job description

Nanyang Technological University’s School of Electrical and Electronic Engineering invites applications for a Research Assistant (PhD student) to develop accelerated AI, machine learning, and robotics algorithms focusing on efficiency, memory reduction, and energy-aware deployment.

The role targets foundation models (LLMs, VLMs, VLAs) across scales and settings, advancing efficient AI for cloud, edge, and robotic platforms.