job description
Join Nanyang Technological University (NTU), a globally recognized leader in engineering and AI research, as a Research Associate in Large Vision Language Models (VLMs). This is a unique opportunity to contribute to cutting-edge advancements in adversarial machine learning, multimodal AI, and computer vision while collaborating with a dynamic, interdisciplinary team.
Based in Bali, Indonesia, this role offers a flexible, remote-first work environment with periodic on-site collaboration in Singapore. You’ll work on high-impact projects that push the boundaries of AI robustness, scalability, and real-world applications, with opportunities to publish in top-tier conferences (e.g., NeurIPS, CVPR, ICML).
NTU’s School of Electrical and Electronic Engineering (EEE) is at the forefront of AI innovation, and this position is ideal for researchers passionate about solving complex challenges in large-scale model training, adversarial attacks/defenses, and vision-language integration.
Responsibility
- Conduct original research on Large Vision Language Models (VLMs), focusing on adversarial robustness, efficiency, and generalization.
- Develop and evaluate novel algorithms for multimodal AI, including vision-language alignment and zero-shot learning.
- Collaborate with cross-functional teams to design scalable AI systems for real-world applications (e.g., autonomous systems, healthcare, robotics).
- Implement and optimize deep learning models using frameworks like PyTorch, TensorFlow, or JAX.
- Publish research findings in peer-reviewed journals and conferences (e.g., NeurIPS, ICML, CVPR).
- Mentor junior researchers and students, fostering a culture of innovation and knowledge-sharing.
- Stay abreast of emerging trends in AI/ML, particularly in VLMs, diffusion models, and adversarial machine learning.
- Contribute to grant proposals and secure funding for high-impact research projects.
Qualifications
- PhD or Master’s degree in Computer Science, Electrical Engineering, AI, or a related field (or equivalent research experience).
- Proven track record in machine learning research, with publications in top-tier conferences/journals.
- Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, etc.).
- Expertise in vision-language models, adversarial attacks/defenses, or multimodal AI.
- Experience with large-scale model training (e.g., transformers, diffusion models) and distributed computing.
- Familiarity with cloud platforms (AWS, GCP) and GPU-accelerated computing.
- Excellent analytical, problem-solving, and communication skills (written and verbal).
- Ability to work independently and collaboratively in a fast-paced, remote-first environment.