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University of Surrey

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

등록일 : 2026-10-23
마감일
2026.11.06(금) 08:59D-14
기관유형
대학
학력
박사
직군
연구원
국가
영국
전공
컴퓨터/통신,물리/천문/대기
근무지
Guildford
근무유형
풀타임
근무형태
Fixed Term (- March 2028)
근무시간
Full Time
급여액
£38,448 to £43,099 per annum
Organization Logo
기관명University of Surrey
홈페이지https://www.surrey.ac.uk
유형대학

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

The University of Surrey is a global community of ideas and people, dedicated to life-changing education and research.
We have a bold vision of what we want to achieve - shaping ourselves into one of the best universities in the world, which we are achieving through the talents and endeavour of every employee.
Our culture empowers people to achieve this aim and to make a real difference.

The role

Do you want to build the first-ever Foundation Model for air quality? We are looking for a world-class AI researcher to join the FMAI4Air project, a high-stakes mission to revolutionise how we predict air pollution, evaluating its impacts on people’s health and protecting millions of lives.

This isn't just another incremental AI project; we are pioneering a Physics-Informed Multimodal High-Resolution Foundation Model. You will be at the intersection of deep learning and atmospheric sciences, working within the prestigious and word-leading ecosystem of Surrey's PAI, CVSSP and GCARE, under the leadership of Assoc Prof Erick Sperandio. Your role will be:

  • Architect the Future of AI for Environmental Sciences: Design and pre-train a novel, task-agnostic, multimodal, high-resolution and physics-informed Foundation Model (FM) for air quality prediction that fuses heterogeneous data, from satellite imagery and surface sensors to meteorological grids and emissions inventories, and evaluates the impacts of air pollution on people’s health.
  • Bridge AI and Atmospheric Physics: Move beyond the "black box" by embedding physical constraints (such as advection-diffusion equations) directly into the model architecture to ensure scientific consistency, interpretability and trustworthiness.
  • Push the Resolution Limit: Implement state-of-the-art super-resolution and downscaling techniques to translate coarse global data into street-level, actionable insights.
  • Solve Real-World Grand Challenges: Fine-tune the pretrained FM for critical downstream applications, including early-warning systems for wildfires and simulating urban air-quality mitigation scenarios to inform government policy through a web-based application for FMAI4Air proof-of-concept.
  • Leverage High-Performance Computing: Pretrain and fine-tune the models on world-leading HPC infrastructure, including Surrey’s AI@Surrey and the national Isambard-AI HPC.
  • Collaborate Nationally and Globally: You will work alongside a powerhouse consortium including Imperial College London, the University of Manchester, and NTNU (Norway), as well as with consortium partners from academia including IAG-USP (Brazil), NC Climate Office at NCSU (USA), Chiba University (Japan), from industry including NVIDIA and WSP Global, and from government such as Guildford Borough Council.

About you

  • Expertise in designing and training large-scale Deep Learning architectures (e.g., Transformers, Mamba, or similar spatiotemporal models).
  • Proven experience in multimodal data fusion (handling a mix of time-series, imagery, and tabular data).
  • Strong proficiency in PyTorch and Tensorflow, and experience deploying models on HPC clusters and on the edge for fast and efficient inference.
  • Expertise in developing and deploying Web applications that will be used to operationalise FMAI4Air models for policy and decision making.
  • A solid mathematical foundation in calculus and linear algebra, with the ability to implement physics-informed constraints into neural networks’ loss functions.
  • A track record of publishing high-quality research in top-tier AI or environmental science conferences/journals.
  • Commitment to deliver high-quality research and innovation outcomes, including publishing papers in top-tier venues, and support research, dissemination, communication and management activities.

How to apply

To apply please submit your CV and a cover letter via our website.

For an informal conversation about the role please contact Erick Sperandio via erick.sperandio@surrey.ac.uk

Further details

Job Description

For more information and to apply online, please download the further details and click on the 'apply online' button above.

In return we offer a generous pension, relocation assistance where appropriate , flexible working options including job share and blended home/campus working locations (dependent on work duties), access to world-class leisure facilities on campus, a range of travel schemes and supportive family friendly benefits including an excellent on-site nursery.

Click here to find out more about the benefits we offer to support you.

The University of Surrey is committed to providing an inclusive environment that offers equal opportunities for all. We place great value on diversity and are seeking to increase the diversity within our community. Therefore we particularly encourage applications from under-represented groups, such as people from Black, Asian and minority ethnic groups and people with disabilities.

Job Details

Department

Centre of Vision, Speech & Signal Processing

Location

Guildford

Salary

£38,448 to £43,099 per annum

Contract

Fixed Term (- March 2028)

Post Type

Full Time

Closing Date

23.59 hours GMT on Thursday 05 November 2026

Reference

051126

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2026-10-23
마감일
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2026-11-06
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