GCARE Research Fellow in Air Pollution Modelling & Monitoring

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The Role

Applications are invited from enthusiastic and talented individuals at the post-doctorate research level to work at the Global Centre for Clean Air Research (GCARE; www.surrey.ac.uk/gcare), University of Surrey, UK, under the supervision of Professor Prashant Kumar. GCARE is a multidisciplinary centre, researching in areas of air pollution, air-climate interactions, built and natural environments in the context of cities, megacities and rural areas, with an aim to develop engineering-driven solutions and regulatory strategies for mitigation of environmental risks by means of advanced measurements and modelling techniques. The GCARE’s research projects are funded by the UKRI, numerous national and international funding bodies and the industry. 

We are looking for a researcher with a PhD degree (or who will receive a PhD degree soon) in the fields of civil, mechanical, chemical, environmental, data science, computer or transportation engineering, physics, chemistry or mathematical sciences or related disciplines.

You will contribute to the GP4Streets project (DIY Greening Prescription for Climate Adaptation in Urban Streets) and support ongoing projects such as the UKRI GREENIN Network Plus, British Council SMARTCOAT, and various air quality consultancy projects. As part of the Guildford Living Lab, you will promote GCARE’s research locally, nationally, and internationally and assist with developing new grant applications. Based at the University of Surrey’s GCARE, you will work closely with GCARE team members and project collaborators and may undertake short visits to partner institutions for collaborative research activities.

The postholder must have strong skills in air pollution/urban heating monitoring and computational modelling (ENVIMET, CFD), remote sensing, and big data analysis. Responsibilities include monitoring and modelling the effectiveness of green infrastructure in mitigating air pollution and urban overheating, with advanced statistical data analysis skills (e.g., R, Python, MATLAB) required. The role calls for a self-driven, independent individual who can log, clean, share, assess, interpret, and write data efficiently to publish in top-tier journals. A proven track record of timely report writing is essential.

The post is available from 01 December 2026. 

How to apply

Please submit an online application that includes the following:

• A maximum one-page cover letter explaining your motivation for joining this post and mapping your skills to the job profile and responsibilities.
• A maximum two-pages CV detailing your education (including grades) and scientific achievements.
• A maximum of two-pages list of your journal and conference publications, along with any reports written. Please include a brief description (no more than 150 words) of your two best publications, highlighting the scientific breakthroughs and skills used or developed.
• Two references, including one from your PhD advisor, if possible.

 For informal enquiries, please contact Professor Prashant Kumar at p.kumar@surrey.ac.uk.  

Further details

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

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