PhD Studentship: Fully Funded PhD Scholarship: Forecasting Future Environmental Impacts of Photovoltaic (PV) Manufacture Using Machine Learning Techniques

Funding providers: Swansea University's Faculty of Science and Engineering, and STRIP5 Prosperity Partnership

Subject areas: Environmental Science, Engineering, Maths, the Physical Sciences

Project start date: 

• 1 July 2024 (Enrolment open from mid-June)
• 1 October 2024 (Enrolment open from mid-September) 

Project description: 

This PhD will suit applicants who are keen to make a difference in how we utilise advanced materials in a sustainable economy. Applicants with undergraduate degrees in Environmental Science, Engineering, Maths or the Physical Sciences will be suited to the position. The research focus can be adjusted depending on the experience of the successful candidate.

This project tackles the challenge of predicting environmental impacts in solar panel manufacturing where the number of data sets available for some of the materials and processes are limited. This is critical to accelerate progress to lower emission manufacturing of renewable technologies.

The focus of the project will be to leverage innovative machine learning (ML) techniques adept at handling sparse information. The impact of data pre-processing techniques will be assessed with the aim of improving the accuracy of predictions. Databases of known materials will be used for validation.

The key objective is to develop a predictive model for cradle to grave environmental impacts of third generation PV which can adjust for different manufacturing location, policy decisions, economic situations etc. This is an ambitious target, and the objective will be split up into separate device components (eg substrate / electrode / active material) and lifecycle stages to enable the student to succeed in their studies even if they are only able to achieve a portion of the model.

This research aims to pioneer adaptable methodologies, providing actionable insights for sustainable PV manufacturing. By creatively leveraging available data and embracing adaptive approaches, the project aims to contribute to sustainable practices within developing manufacturing industries.

Eligibility 

Candidates must hold an Upper Second Class (2.1) honours degree in Engineering or similar relevant science discipline. If you are eligible to apply for the scholarship (i.e. a student who is eligible to pay the UK rate of tuition fees) but do not hold a UK degree, you can check our comparison entry requirements. Please note that you may need to provide evidence of your English Language proficiency. 

Applicants with undergraduate degrees in Environmental Science, Engineering, Maths, or the Physical Sciences will be suited to the position.  

Due to funding restrictions, this scholarship is open to applicants eligible to pay tuition fees at the UK rate only, as defined by UKCISA regulations.

Additional Funding Information

This scholarship covers the full cost of UK tuition fees and an annual stipend at UKRI rate (currently £18,662 for 2023/24).

Additional research expenses will also be available.