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University of Surrey

Research Fellow in Computational Modelling of Energy Geotechnics

Guildford
£37.6k – £40k/yr
Posted about 24 hours ago
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The University of Surrey

The University of Surrey is a global community of ideas and people, dedicated to life-changing education and research.

We are ambitious and 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 collectively, and individually, make a real difference.

The role

We are looking for an enthusiastic and highly motivated researcher to join an EPSRC-funded UKRI-Norway project on Energy Micropile Retrofits for Climate Change Adaptation of Existing Buildings. This is an exciting opportunity to contribute to research at the interface of computational geotechnics, data-centric methods, sustainable infrastructure, low-carbon energy systems, and climate-change adaptation.

The project aims to develop and validate energy micropile retrofit solutions that can support the decarbonisation of existing buildings by combining structural foundation performance with renewable thermal energy exchange. Based within the University of Surrey's School of Engineering, the successful candidate will lead the project's computational modelling strand, developing complex numerical models and validating them against datasets generated by collaborators. The candidate will use surrogate modelling and data-centric approaches to complement simulations, incorporating uncertainty to evaluate system resilience, and developing useful tools that will enable industry to adopt energy micropiles as a dual structural–energy retrofit solution.

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This research will be performed in close collaboration with colleagues at the University of Surrey and with project partners at the Universities of Leeds, Cambridge and NTNU, as well as relevant industrial collaborators. The role offers the opportunity to undertake cutting-edge computational research, contribute to high-impact publications, and engage with a multidisciplinary consortium addressing an important challenge in sustainable infrastructure.

In this role, the successful candidate will:

  • Develop and validate advanced numerical models of energy micropiles
  • Undertake large-scale simulations and data-driven analysis to explore performance and optimise designs
  • Assess the impact of uncertainty on retrofit outcomes
  • Translate research findings into practical tools and guidance for industry

The role also involves contributing to publications, conferences, technical reports, and collaborative project activities, and would suit a researcher with strong computational, numerical modelling, and programming skills who is motivated by real-world climate and energy challenges.

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About You

The successful candidate will have a PhD, or be near completion of a PhD, in Geotechnical Engineering, Civil Engineering, Mechanical Engineering, Geo-energy, Energy Systems, Computational Mechanics, or a related discipline. You will have experience with numerical modelling and/or data-centric methods and a keen interest in applying these to energy and infrastructure challenges.

You should be able to demonstrate experience in numerical modelling of coupled thermal, hydraulic, and/or mechanical processes, alongside strong scientific programming, data-handling, and analytical skills. Experience in probabilistic analysis and uncertainty quantification within an engineering context, a track record of high-quality peer-reviewed research, and the ability to work independently and collaboratively are also essential, together with strong communication and problem-solving skills and a willingness to travel occasionally within the UK and internationally.

How To Apply

To apply, please submit an online application via the University of Surrey jobs website, including your CV and a covering letter (maximum length of 2 pages) that sets out how you meet the criteria for the role.

For an informal discussion about the role, please contact: Dr Nikolas Makasis (n.makasis@surrey.ac.uk)

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Skills

Computational Modelling
Numerical Modelling
Data-Centric Methods
Surrogate Modelling
Uncertainty Quantification
Scientific Programming
Probabilistic Analysis
Geotechnical Engineering
Thermal-Hydraulic-Mechanical Coupling
Data Handling
Analytical Skills
Problem Solving
Technical Writing
Collaborative Research

Location

Guildford, England, United Kingdom

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