job description
Join Nanyang Technological University (NTU) as a Research Fellow in Multimodal Intelligence and lead groundbreaking research at the intersection of AI, machine learning, and human-computer interaction. Based in the vibrant and innovative hub of Bali, Indonesia, this role offers a unique opportunity to shape the future of multimodal systems while collaborating with a global network of researchers and industry leaders.
As a Research Fellow, you will drive high-impact projects, publish in top-tier conferences, and mentor the next generation of AI talent. NTU is renowned for its cutting-edge research in AI and multimodal intelligence, and this position allows you to contribute to transformative technologies that bridge text, vision, audio, and beyond.
Whether you're developing novel algorithms, designing multimodal models, or exploring real-world applications in healthcare, robotics, or smart cities, your work will have a lasting impact. Enjoy the flexibility of remote work with occasional on-site collaboration in Bali’s dynamic tech ecosystem, where creativity and innovation thrive.
Responsibility
- Lead and execute cutting-edge research in multimodal intelligence, including vision-language models, cross-modal understanding, and generative AI.
- Publish high-quality papers in top-tier conferences and journals (e.g., NeurIPS, ICML, CVPR, ACL).
- Develop and optimize multimodal AI models for real-world applications in collaboration with industry and academic partners.
- Mentor and supervise PhD and Master’s students, fostering a culture of innovation and excellence.
- Contribute to grant proposals and funding applications to secure resources for research initiatives.
- Collaborate with interdisciplinary teams to integrate multimodal AI into domains like healthcare, robotics, or smart systems.
- Stay abreast of emerging trends in AI, machine learning, and multimodal research, and apply insights to ongoing projects.
- Present research findings at international conferences, workshops, and industry events.
Qualifications
- PhD in Computer Science, AI, Machine Learning, or a related field (or equivalent research experience).
- Proven track record of publications in top-tier AI conferences/journals (e.g., NeurIPS, ICML, CVPR).
- Strong expertise in multimodal AI, deep learning, or generative models (e.g., transformers, diffusion models).
- Experience with large-scale datasets, model training, and evaluation in multimodal settings.
- Proficiency in Python, PyTorch, TensorFlow, or similar frameworks for AI/ML development.
- Excellent written and verbal communication skills for publishing and presenting research.
- Ability to work independently and collaboratively in a fast-paced, interdisciplinary environment.
- Passion for mentoring students and contributing to a thriving research community.