Research Fellow – Embodied AI & Multimodal LLMs

About the role

The School of Mechanical & Aerospace Engineering at NTU seeks a Research Fellow to drive advancements in embodied artificial intelligence. The role focuses on developing multimodal large language models that integrate vision, language and action to enable seamless human‑robot interaction and autonomous task execution.

Key responsibilities

• Publish high‑quality research in top‑tier conferences and journals.
• Design and implement multimodal LLM architectures that combine vision, language and action for embodied AI systems.
• Develop and optimise deep‑learning algorithms that allow robotic arms to perform complex tasks guided by natural‑language instructions.
• Experiment with and deploy vision‑language‑action models on robotic platforms.
• Collaborate with a multidisciplinary team to advance embodied intelligence research.

Required profile

• Ph.D. in Computer Science, Robotics, AI or a related discipline.
• At least three first‑author publications in top AI or robotics conferences.
• Demonstrated expertise in deep learning, multimodal LLMs and Vision‑Language‑Action models.
• Strong programming experience in Python and PyTorch.
• Hands‑on experience with robotic systems, particularly robotic arms.
• Familiarity with human‑robot interaction and reinforcement learning is a plus.

Required skills

• Python
• PyTorch
• Deep learning
• Multimodal large language models
• Vision‑Language‑Action modeling
• Robotic arm manipulation
• Reinforcement learning (optional)