Fully Funded Phd Position: Artificial Intelligence For Photovoltaics

ScholarLink Inc.; Australia; Presencial; AUD 36.000 - 45.000; Jornada completa

Descripción de la vacante

Australian National University is offering a fully funded PhD studentship in Artificial Intelligence for Photovoltaics within the School of Engineering in Australia. The position includes a tax-free AU$40,475 annual stipend and full tuition waiver, with access to top-tier computational and fabrication facilities.

Ideal candidates have strong CS or PV backgrounds, with high academic standing and proven research achievements.

Formación

• Strong background in Computer Science or Silicon Photovoltaics.
• International applicant should rank within top 5% of graduating class.
• GPA/papers/patents demonstrating research excellence as proof of capability.

Responsabilidades

• Develop physics-informed machine learning models for photovoltaic analytics.
• Analyze outdoor measurement data and laboratory characterization data.
• Collaborate with industry partners and publish research findings.

Conocimientos

Python programming

Data analysis

Machine learning

Photovoltaic modeling

Experimental research

Descripción del empleo

# Fully funded PhD position: Artificial Intelligence for PhotovoltaicsPh.D·Australian National University·School of Engineering·AustraliaFunding: 40475 USD per yearPosition type: StudentshipLevel: Ph.DDuration: 4 yearsLanguage: EnglishLimited to Australia, New Zealand## About the PositionIf you are passionate about the application of AI in engineering science, we invite you to join us to shape the future of photovoltaics (PV) technologies together at the Australian National University (QS ranking 2026: No. 32 World-wide)!Contact: Marco ErnstWebsite: https://www.marcoernst.com/Our PhD students are publishing in top-tier journals such as Advanced Materials, Advanced Functional Materials, etc. Only top students will be considered!Eligible and Selection CriteriaApplicant is expected to have a strong background in Computer Science or Silicon Photovoltaics.Academic Excellence (see ANU admission requirements for further details):International applicant should rank within the top 5% of their graduating class from a highly regarded university.Australian and New Zealand applicant should hold at least an Upper Second-Class Honours (H2A) or equivalent qualification.Research Achievements (applicants with a GPA below 3.2 / 4.0 must demonstrate research excellence through one of the following):At least one first-authored publication in a high-impact journal or conference (e.g., Impact Factor ≥ 20, NeurIPS, ICML, etc.), orAt least three first-authored publications in high-quality journals or conferences (e.g., Impact Factor ≥ 5), orAt least three patents.FundingThe successful candidate will receive an annual tax-free stipend of AU$40,475 per annum (Full-time base rate 2027) together with a full tuition waiver.The project is fully supported through the lead supervisor's active research grants.Research ResourcesThe successful candidate will have access to state-of-the-art computational and experimental facilities, enabling cutting-edge research at the interface of AI and photovoltaics.Computational ResourcesHigh-performance workstations featuring high-performance CPU and GPU, including AMD Threadripper 7970X, AMD Threadripper Pro 7965WX, NVIDIA RTX PRO 5000 Blackwell, NVIDIA RTX 4090, and more.Access to National Computational Infrastructure (NCI) and ARDC's Nectar Research Cloud.Experimental ResourcesWorld-class silicon photovoltaic fabrication and characterisation laboratories, where world-record solar cells have been demonstrated.Access to national-level facilities, including the Australian National Fabrication Facility (ANFF), for device fabrication and advanced materials characterisation.Collaboration NetworksEmbedded within the Australian Centre for Advanced Photovoltaics (ACAP), with the ANU group as a key member.Broad intern## Research Interests* Develop physics-informed machine learning models for photovoltaic analytics* Analyze outdoor measurement data and laboratory characterization data* Investigate long-term performance and degradation of solar PV modules* Collaborate with industry partners and present research findings## Required Skills & Qualifications* Python programming* Data analysis* Machine learning* Photovoltaic modeling* Experimental research## Other Requirements & Additional InfoThe project involves developing physics-informed machine learning and data-driven methods for photovoltaic module analytics, combining outdoor measurements with laboratory and accelerated testing data, focusing on long-term performance prediction and degradation behavior.