[School of Natural Sciences PhD Scholarships] Multiscale mathematical modelling for underground energy storage

About the project

About the Project Underground gas storage, including hydrogen storage, is emerging as a pivotal solution in the transition to a sustainable clean-energy economy. Repeated injection and withdrawal drive transport through complex porous structures, while the overlying caprock must prevent gas escape. Indeed, hydrogen is known as the ‘Houdini gas’ due to its high mobility. Predicting this behaviour requires mathematical models that connect microscopic physics with reservoir-scale dynamics and account for uncertainty in the underlying structure and transport properties. Working with Dr Igor Chernyavsky and Prof. Oliver Jensen (Mathematics), the doctoral researcher will develop and analyse hybrid mathematical models of gas transport in heterogeneous porous media, combining multiscale methods with uncertainty quantification. The theoretical work will be informed by advanced 4D imaging of porous formations from Dr Lin Ma’s group (Chemical Engineering), alongside ultra-precision measurements of atomic and molecular gas flows in collaboration with Prof. Radha Boya (Physics). Open questions include how to derive effective large-scale descriptions from small-scale physics, how cyclic forcing influences gas migration, and how uncertainty propagates into predictions of storage performance and containment. Particular attention will be paid to experimentally observed anomalous transport and rare events that could compromise storage integrity. The project offers a unique opportunity to investigate fundamental questions in multiscale transport while addressing an important challenge in energy storage and other geophysical applications. It is particularly suited to students interested in applied mathematics, theoretical physics and the interplay between analysis, modelling and experiment. This project is expected to start in September 2027. Before you apply: We strongly recommend that you contact the supervisors for this project before you apply. How to apply: To be considered for this project you must complete a formal application through our online application portal. If you already have an applicant account this link will directly open an application for PhD School of Natural Sciences Scholarships . If you don’t already have an applicant account, please follow the instructions here . When applying, please specify the full title and supervisor/s of the project, details of your previous study, and names and contact details of two referees. You must also upload a Supporting Statement describing your motivation to apply to the project, your CV and transcripts of awarded and in-progress university qualifications . Please note late or incomplete applications will not be considered. Equality, diversity and inclusion are fundamental to the success of The University of Manchester and central to all our activities. A diverse research community strengthens creativity, productivity and quality, while increasing the societal and economic impact of our work. We welcome applicants from all career paths, backgrounds and sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation or transgender status. We welcome applications from candidates returning to study after a career break or experience in other roles. Flexible study arrangements may be available, including part-time study at 50%, 60% or 80%, subject to the requirements of the project and funder. Eligibility : The standard academic entry requirement for this PhD is an upper second-class (2:1) honours degree (or international equivalent) in Mathematics or a closely related discipline OR any upper-second class (2:1) honours degree and a Master’s degree at merit (or international equivalent) in Mathematics or a closely related discipline. The ideal candidate would have: A strong grounding in applied mathematics, particularly differential equations and mathematical modelling. Experience in scientific computing methods for mathematical models, using Python, MATLAB, Julia or C++. Evidence of successful engagement in an individual research project. Excellent time-management skills. - Keen interest in working within a multidisciplinary team. Desirable qualities: Knowledge of theoretical fluid or continuum mechanics, or the physics of porous media. Knowledge of asymptotic analysis of differential equations. Experience in image analysis or uncertainty quantification. This project will remain open until filled. If your application is submitted by 1st November 2026, you can expect a decision by 18th December 2026. If your application is submitted by 15th January 2027, you can expect a decision by 30th March 2027. Self or externally funded students can also be considered for this project. FSESoNS

Research areas