Research Fellow (Multimodal LLM in Robotics)

The School of Mechanical & Aerospace Engineering (MAE) is a robust, dynamic and multi-disciplinary international research community comprising of world-class scientists and bright students. MAE prides itself in its excellent research capabilities in areas including advanced manufacturing, aerospace, biomedical, energy, industrial engineering, maritime engineering, robotics, etc. The school is equipped with state-of-the-art research infrastructure, housing a comprehensive range of cluster laboratories, test bedding facilities, research centres/institutes and corporate laboratories. Cutting-edge research in MAE addresses the immediate needs of our industries and supports the nation’s long-term development strategies. In the new era of industrial 4.0 and sustainable living, MAE is rigorous in developing new competencies to support the growth and competitiveness of our engineering sector in the global landscape. MAE has grown to be leader in Engineering Research, ranking amongst the top engineering schools in the world.

For more details, please view https://www.ntu.edu.sg/mae/research.

Position Overview
We are seeking a highly motivated Postdoctoral Research Fellow to join our research team focusing on integrating multimodal large language models (LLMs) with embodied AI. This position will involve the development and deployment of Vision-Language-Action models for real-world robotic applications, such as autonomous task execution and human-robot interaction. The successful candidate will work on cutting-edge research at the intersection of AI, robotics, and multimodal learning.

Key Responsibilities

• Design and implement multimodal LLM architectures that integrate vision, language, and action for embodied AI systems.

• Develop and optimize deep learning algorithms to enable robotic arms to perform complex tasks guided by natural language instructions.

• Utilize PyTorch to train and fine-tune models on multimodal datasets.

• Experiment with and deploy vision-language-action models on robotic platforms.

• Collaborate with a multidisciplinary team to advance the field of embodied intelligence.

• Publish high-quality research in top-tier conferences and journals.

Qualifications

• Ph.D. in Computer Science, Robotics, AI, or a related field.

• Expertise in deep learning, multimodal LLMs, and Vision-Language-Action models.

• Strong programming skills in Python, with significant experience in PyTorch.

• Hands-on experience with robotic systems, particularly robotic arms.

• Familiarity with human-robot interaction and reinforcement learning is a plus.

• Demonstrated ability to conduct independent research and contribute to collaborative projects.

We regret to inform that only shortlisted candidates will be notified.