Research Fellow in Multimodal Physics-Informed Foundation Model for Air Quality Applications

Overview

The University of Surrey is hiring a Research Fellow to join the Centre of Vision, Speech and Signal Processing for the FMAI4Air project. The role focuses on building a multimodal physics-informed foundation model for air quality applications to predict air pollution, evaluate health impacts, and protect lives. The position is based on site in the United Kingdom.

Who can apply

Candidates must be world-class AI researchers with expertise in designing and training large-scale deep learning architectures, such as Transformers or Mamba spatiotemporal models. Applicants need proven experience in multimodal data fusion handling time-series, imagery, and tabular data, along with strong proficiency in PyTorch and TensorFlow. Additional requirements include experience deploying models on HPC clusters and edge systems, expertise in developing and deploying web applications for policy and decision-making, and a solid mathematical foundation in calculus and linear algebra to implement physics-informed constraints. Candidates should also have a track record of publishing high-quality research in top-tier AI or environmental science conferences and journals, and a commitment to delivering research and innovation outcomes.

What you get

The position offers a full-time, fixed-term contract with a salary ranging from £38,448 to £43,099 per annum. The role involves working within Surrey's PAI, CVSSP, and GCARE ecosystem, leveraging high-performance computing infrastructure including AI@Surrey and Isambard-AI HPC, and collaborating with a national and global consortium of academic, industry, and government partners.

How to apply

Interested candidates must submit a curriculum vitae and a cover letter through the university website. Applicants seeking an informal conversation about the role can contact Erick Sperandio by email.

Key dates

The closing date for applications is 2026-11-05.