PhD on artificial intelligence for renewable energy and sustainability

Renewable energy sources have gained increased attention and investments from the industries, governments and society, such as wind, solar, and hydrological sources, to enable a more sustainable and yet economically feasible development. However, the building and operationalization of renewable power plants face a series of challenges that must be tackled in order to improve their adoption. One of the main challenges resides in the ability to accurately predict the meteorological parameters that influence the generation of wind and solar energy from shorter to longer term, which becomes even more challenging in the face of climate change.

Therefore, this project aims at researching, developing and building AI-based solutions that can support the development of more reliable and accurate weather forecasting systems applied to the prediction of solar and wind energy generation, extreme weather events forecasting and their effects, air quality and sustainability. Historical data from publicly available sources will be used, like surface weather stations, GDAS/ECMWF/Era5 and satellite data, among others, along with information about wind turbines and photovoltaic cells.

We seek for exceptional candidates that are willing to develop AI-based clean air solutions by researching and building cutting-edge approaches and techniques in the fields of deep learning, physics-informed and graph neural networks, spatial-temporal modelling, model explainability and interpretability, time series foundation models, physical modelling and data-driven approaches, among others, applied to the challenges related to the fields of renewable energies and sustainability.

The applicant will be directly involved with research activities in the Global Centre for Clean Air Research (GCARE) and the People-Centred AI Institute, both in the University of Surrey, having access to an amazing set of resources, infrastructure and people engaged to deliver world-class researches and technologies with a focus on the well-being of people and on the scientific and technological development of the academia, industry and society.

This studentship is open to UK and international candidates.

All applicants should have (or expect to obtain) a first-class degree in a numerate discipline (mathematics, science or engineering) or MSc with distinction (or 70% average) and a strong interest in pursuing research in this field.

Additional experience which is relevant to the area of research is also advantageous.

English language requirements

IELTS minimum 6.5 overall with 6.0 in writing, or equivalent.