At a Glance
- Tasks: Join a leading research team to develop AI and machine learning for innovative solar technologies.
- Company: UNSW, a world-leading institution in renewable energy research.
- Benefits: Competitive salary, professional development, and a collaborative work environment.
- Other info: Dynamic role with opportunities for conference participation and student supervision.
- Why this job: Make a real impact on sustainable energy solutions while advancing your academic career.
- Qualifications: PhD or postdoc experience in AI, ML, or related fields; strong research skills required.
The predicted salary is between 126711 - 126711 £ per year.
This position is based in Australia. 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.
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.
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.
Additional details about the specific responsibilities for these positions can be found in the position description. This is available via JOBS@UNSW. 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.
Contact:
- For role-specific inquiries, please contact Prof Xiaojing Hao E: xj.hao@unsw.edu.au
- For questions regarding the recruitment process, please contact Allyssar Hamoud (Talent Acquisition Associate) E: a.hamoud@unsw.edu.au
Position Description Advertised: 27 Jul 2026 AUS Eastern Standard Time Applications close: 26 Aug 2026 AUS Eastern Standard Time.
Postdoctoral Fellow in AI and Machine Learning for Photovoltaics in Moscow employer: UNSW
UNSW is an exceptional employer, offering a dynamic and inclusive work culture that prioritises equity and diversity. As a part-time Research Associate at The Kirby Institute, you will have the opportunity to engage in meaningful research that impacts public health while collaborating with leading experts in a supportive environment. With a focus on employee growth and development, UNSW provides unique advantages such as flexible hybrid working arrangements and access to cutting-edge resources.
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We think you need these skills to ace Postdoctoral Fellow in AI and Machine Learning for Photovoltaics in Moscow
Some tips for your application 🫡
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Craft a Compelling Cover Letter:Use your cover letter to express your passion for engineering and explain why you’re drawn to UNSW specifically. Share what aspects of their work excite you and how your values align with theirs. This is your chance to show a bit of personality while keeping it professional!
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How to prepare for a job interview at UNSW
✨Brush Up on Core Engineering Principles
Before heading into the interview with UNSW, make sure you're solid on the fundamental engineering principles relevant to the role. Be ready to discuss concepts such as thermodynamics, fluid mechanics, or structural analysis, depending on the specifics mentioned in the job description. Don’t skip any hands-on projects or coursework; these can be excellent talking points!
✨Show Off Your Problem-Solving Skills
Expect technical questions or case studies during your interview—after all, engineering is all about solving problems! Prepare a few examples of how you've tackled engineering challenges in the past, whether at university or in any practical experience. Practising with mock technical interviews can really help you articulate your thought process and solutions.
✨Relate Your Experience to the Role
In a full-time role, employers like UNSW want to see that you can adapt and grow within their team. Be ready to discuss how your previous internships, projects, or studies relate directly to the work you'll be doing. Highlight specific experiences that showcase your collaborative skills and how you've successfully worked within a team environment.
✨Know Your Tools and Software
Most engineering roles require familiarity with specific tools and software. Prepare to talk about your proficiency with programmes like AutoCAD, MATLAB, or SolidWorks if they’re relevant to the role. Even better, have examples of projects where you’ve used these tools, as it'll demonstrate your hands-on experience and readiness for the job.
