Postdoctoral Fellow in AI and Machine Learning for Photovoltaics

13 ago - Italia
UNSW

This Job is based in Australia

The Opportunity
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.
- Salary, Level A - AUD (118,467 to )126,711 per annum + 17% superannuation
- Tempo pieno
- Fixed-term contract – 1 year (with the possibility of extension for another 4 years)
- Location: Kensington – Sydney, Australia

About UNSW
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. For academics, UNSW offers an outstanding platform to flourish — combining world‑class facilities, collaborative networks, and a culture of innovation that supports both career growth and meaningful contributions to the wid

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