NUS Teams Up With Applied Materials to Inject AI Into Semiconductor R&D

The National University of Singapore has partnered with Applied Materials to use artificial intelligence to speed up semiconductor process development while building a specialised talent pipeline for AI-driven manufacturing. The collaboration, formalised at the opening of Applied Materials' new Tampines campus, will focus on using AI to reduce the trial-and-error cycles involved in developing and optimising semiconductor materials and processes.

Under the partnership, AI models will be trained on experimental and equipment-generated data to identify and prioritise the next set of experiments, creating a feedback loop that accelerates the transition from laboratory research to production environments. The work will take place within the Applied Materials-NUS Advanced Materials Corporate Lab, established in 2018 and expanded in 2024, which already combines applied chemistry, materials science, and semiconductor process engineering research.

On the talent side, NUS will launch a new postgraduate specialisation in Applied AI for Materials and Process Engineering under its Master of Science in Semiconductor Technology and Operations programme from August 2026. The course will cover machine learning, computer vision, and generative AI, with applications in defect detection, predictive maintenance, and yield optimisation — skills that Singapore's growing semiconductor ecosystem urgently needs as facilities like the Applied Materials campus come online.

The collaboration is supported by a S$3 million endowed gift from Applied Materials and runs alongside a separate partnership with the Singapore Institute of Technology that includes the institution's first industry-based professorship and a scholarship programme for engineering undergraduates. NUS deputy president Professor Aaron Thean described the initiative as reflecting the university's effort to integrate AI more directly into both semiconductor research and training, while Applied Materials' Prabu Raja noted that combining academic research with industrial data can significantly reduce development cycles.

Why it matters for Singapore: The NUS-Applied Materials partnership represents a rare end-to-end approach to AI in manufacturing — connecting foundational research, applied AI development, and talent pipeline creation within a single framework. For Singapore's broader strategy of becoming a semiconductor and advanced manufacturing hub, this type of industry-academia collaboration is essential. It ensures that as new facilities like the Tampines campus come online, there are Singapore-trained engineers ready to run them, equipped with AI skills that go beyond traditional manufacturing know-how.