UNSW
Postdoctoral Fellow in AI and Machine Learning for Photovoltaics
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Postdoctoral Fellow in AI and Machine Learning for Photovoltaics
Job no: 541338
Work type: Full Time
Location: Sydney, NSW
Categories: Post Doctoral Research Associate
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
- Full time
- 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 wider community.
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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 our labs in 1983 and today powers more than 85% of all new solar panel modules all over the world. SPREE’s work and people have changed the face of sustainable energy on the global stage, and we continue to be at the forefront of leading-edge research and development in the field of renewable technology as our economies transition away from fossil fuels. For more information, please see the following link: https://www.unsw.edu.au/engineering/our-schools/photovoltaic-and-renewable-energy-engineering
Skills & Experience
- 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.
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Additional details about the specific responsibilities for these positions can be found in the position description. This is available via JOBS@UNSW.
To Apply
Please click the “Apply Now” button and submit your CV, Cover Letter and Responses to the Skills and Experience. You should systematically address the Skills and Experience listed within the position description in your application.
Please note applications will not be accepted if sent to the contact listed below.
Contact:
For role-specific inquiries, please contact Prof Xiaojing Hao
For questions regarding the recruitment process, please contact Allyssar Hamoud (Talent Acquisition Associate)
Applications close: 11:55 pm (Sydney time) on Wednesday 26th August 2026
As part of our recruitment process candidates may be required to undergo pre-employment screening, which may include reference checks, qualification verification, right-to-work verification, and criminal history screening where relevant to the role.
UNSW is committed to evolving a culture that embraces equity and supports a diverse and inclusive community where everyone can participate fairly, in a safe and respectful environment. We welcome candidates from all backgrounds and encourage applications from people of diverse gender, sexual orientation, cultural and linguistic backgrounds, Aboriginal and Torres Strait Islander background, people with disability and those with caring and family responsibilities. UNSW provides workplace adjustments for people with disability, and access to flexible work options for eligible staff. The University reserves the right not to proceed with any appointment.
Position Description
Advertised: 27 Jul 2026 AUS Eastern Standard Time
Applications close: 26 Aug 2026 AUS Eastern Standard Time
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