Postdoctoral Fellow in AI and Machine Learning for Photovoltaics

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.

Responsibilities

The Postdoctoral Fellow will be responsible for developing predictive and physics-informed models, analysing experimental and operational datasets, and supporting multidisciplinary research activities.

Key responsibilities include contributing to the dissemination of research outcomes, participating in conferences and workshops, and assisting 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.

Qualifications

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.

Skills

Experience in predictive modelling for materials synthesis, machine learning, digital twin development, reliability analysis, or materials informatics for physical systems is preferred.

Highly developed interpersonal skills and the ability to communicate and interact with a diverse range of stakeholders and students.

Benefits

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.

Opportunity to develop your scholarly research and professional activities.

Collaborative research environment.

Access to world-class facilities and resources.

Pay

Salary, Level A - 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).