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About the Role

This role focuses on developing and applying AI, ML, and data-driven methodologies for thin-film and tandem photovoltaic technologies. You will contribute to innovative research, develop predictive models, analyze datasets, and support multidisciplinary research activities. The position offers opportunities for scholarly research, professional development, dissemination of outcomes, conference participation, and student supervision.

Responsibilities

Develop and apply artificial intelligence, machine learning, and data-driven methodologies for emerging thin-film and tandem photovoltaic technologies.
Develop predictive and physics-informed models.
Analyze experimental and operational datasets.
Support multidisciplinary research activities.
Disseminate research outcomes through appropriate channels and outlets.
Participate in conferences and workshops.
Assist with the supervision of research students.

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.

Skills

Artificial Intelligence
Machine Learning
Data Science
Physics
Engineering
Materials Science
Predictive modelling
Digital twin development
Reliability analysis
Materials informatics

Location

Kensington – Sydney, Australia

Work Type

Full time
Fixed-term contract

Experience Level

Postdoctoral Fellow

Education Level

Salary/Compensations

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

Benefits

17% superannuation

About the Company

UNSW is a world-leading institution recognised for its scale, prestige, and impact, with strong industry engagement and partnerships. It provides a unique environment where academic expertise translates into real-world outcomes, driving innovation and societal progress. UNSW offers cutting-edge research facilities, collaborative networks, and a culture of innovation. The School of Photovoltaic and Renewable Energy Engineering (SPREE) is internationally recognised for its record-breaking research in solar power and renewable energy, having invented the PERC solar cell. SPREE is at the forefront of leading-edge research and development in renewable technology.

Equal Opportunity

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.