Artificial Intelligence for Photovoltaics (Fully Funded PhD Position) Australian National University in Australia

Join a pioneering PhD research program at the Australian National University (ANU), ranked No. 32 worldwide (QS 2026), focused on the application of artificial intelligence (AI) in next-generation photovoltaics. This fully funded position is part of the School of Engineering and offers the opportunity to work at the interface of AI, materials science, and solar energy technologies.

The project centers on physics-based AI for perovskite photovoltaics, aiming to address critical challenges such as device stability and efficiency. By leveraging machine learning and computational materials science, the successful candidate will contribute to the rational design and optimisation of perovskite-based solar cells. The group has achieved world-record solar cell performance and regularly publishes in top-tier journals like Nature, Science, and Advanced Materials.

Research resources include access to the National Computational Infrastructure (NCI), high-performance workstations (Intel Core Ultra 9, AMD Threadripper Pro, NVIDIA RTX PRO 5000 Blackwell, RTX 4090), and advanced simulation software (VASP, Gaussian, COMSOL). Experimental facilities feature world-class perovskite photovoltaic fabrication and characterisation labs, as well as Australia’s most advanced high-throughput robotic platform for AI-guided experimentation. Collaboration networks span the Australian Centre for Advanced Photovoltaics (ACAP) and leading institutions in China, Germany, the US, the UK, and Australia.

Eligibility requires a strong background in Computer Science, Computational Materials Science, or Perovskite Photovoltaics. International applicants should be in the top 5% of their graduating class from a highly regarded university; Australian and New Zealand applicants need at least an Upper Second-Class Honours (H2A) or equivalent. Applicants with a GPA below 3.2/4.0 must demonstrate research excellence through high-impact publications or patents. Experience in machine learning and computational materials science is highly preferred.

The position is fully funded, offering an annual tax-free stipend of AUD $39,069 and a full tuition waiver, supported by the supervisor’s active research grants. The successful candidate will work in a collaborative and friendly environment, with opportunities to attend domestic and international conferences. Applications are accepted year-round.

To apply, contact Dr Hualin Zhan at [email protected] with your CV and academic transcripts. For more information, visit the group website at www.nexsas.org or the official position page here.