Postdoctoral Fellow in AI and Machine Learning for Photovoltaics

This role is based in Sydney, NSW, Australia.

About the role

The School of Photovoltaic and Renewable Energy Engineering (SPREE) has an opportunity for a Postdoctoral Fellow to join a leading research team. This role will focus on the development and application of artificial intelligence (AI), machine learning (ML), and data-driven methodologies for emerging thin-film and tandem photovoltaic technologies, contributing to innovative research that supports the advancement of next-generation photovoltaic technologies.

Working within a collaborative research environment, you will help develop predictive and physics-informed models, analyse experimental and operational datasets, and support multidisciplinary research activities. This position will provide you with the opportunity to develop your scholarly research and professional activities. You will contribute to the dissemination of research outcomes through appropriate channels and outlets, participate in conferences and workshops, and assist with the supervision of research students.

This role reports to Scientia Professor Xiaojing Hao and has no direct reports.

Pay

Salary: AUD $118,467 to $126,711 per annum + 17% superannuation.

Schedule

• Full time
• Fixed-term contract – 1 year (with the possibility of extension for another 4 years)

About the organisation

UNSW is a world-leading institution recognised for its scale, prestige, and impact. With strong industry engagement and partnerships across sectors, UNSW provides a unique environment where academic expertise translates into real-world outcomes. The university is home to cutting-edge research that drives innovation and societal progress, while its excellence in teaching ensures students are prepared to lead in their fields.

The School of Photovoltaic and Renewable Energy Engineering is internationally recognised for its record-breaking research in solar power (photovoltaics) and renewable energy. The PERC solar cell was first invented at UNSW in 1983 and today powers more than 85% of all new solar panel modules worldwide. SPREE continues to be at the forefront of leading-edge research and development in renewable technology as economies transition away from fossil fuels.

Requirements

• A PhD or postdoc research experience in Artificial Intelligence, Machine Learning, Data Science, Physics, Engineering, Materials Science, or a closely related discipline, and/or relevant work experience.
• Experience in predictive modelling for materials synthesis, machine learning, digital twin development, reliability analysis, or materials informatics for physical systems is preferred.
• Proven commitment to proactively keeping up to date with discipline knowledge and developments.
• Demonstrated ability to undertake high-quality academic research and conduct independent research with limited supervision.
• Demonstrated track record of publications and conference presentations relative to opportunity.
• Demonstrated ability to work in a team, collaborate across disciplines, and build effective relationships.
• Evidence of highly developed interpersonal skills.
• Demonstrated ability to communicate and interact with a diverse range of stakeholders and students.
• An understanding of and commitment to UNSW’s aims, objectives, and values in action, together with relevant policies and guidelines.
• Knowledge of health and safety responsibilities and commitment to attending relevant health and safety training.