Department of Earth Science and Engineering
Key facts
Research Excellence Framework (REF) 2021
1st in the UK (Engineering) – based on the proportion of world-leading research
The Times and Sunday Times Good University Guide 2022
2nd in the UK
The Department of Earth Science and Engineering straddles the interface between pure science and engineering.
Our research is focused on understanding the fundamental processes that occur on the Earth’s surface down to the planet’s deep interior, and spans three themes:
- earth and planetary science
- natural resources geoscience and engineering
- computational geoscience and engineering
Our work contributes to an understanding of climate change at various temporal and spatial scales; we also aim to meet the challenge of reducing the environmental impact of society’s consumption of natural resources.
We’re also involved in a number of cross-disciplinary and cross-departmental research centres, such as the Grantham Institute and Energy Futures Lab.
The Department collaborates closely with the nearby Natural History Museum, and makes use of their excellent analytical facilities. In addition, we have significant research relationships with Shell, Sinopec, Equinor, TOTAL, BHP, Microsoft. Our key academic partners include NASA, European Space Agency, International Ocean Discovery Programme (IODP), MIT, ETH Zurich, China University of Petroleum Beijing (CUPB).
Our students usually find summer and permanent employment in the major oil and mining companies, as well as in software and consulting businesses; most undertake summer placements in industry to complete their research projects.
Study opportunities
The Department offers a number of study options to help you take your knowledge to the next level.
If you are interested in Doctoral study, it’s important to gain support for your application from your potential supervisor before making a formal application to the College.
Tabbed information block
Master's courses
MSc courses
- MSc Applied Computational Science and Engineering (1 year full-time)
- MSc Environmental Data Science and Machine Learning (1 year full-time)
- MSc Geo-energy with Machine Learning and Data Science (1 year full-time)
- MSc Metals and Energy Finance (1 year full-time)
Research programmes
- PhD Earth Science and Engineering research
(2–4 years full-time; 4–6 years part-time)
- PhD Petroleum Engineering research
(2–4 years full-time; 4–6 years part-time)
Earth and Planets Section
The Earth and Planets research section has a broad interest in Earth system and planetary sciences, with particular strengths in meteorite impacts and astromaterials, surface processes on Earth and Mars, dynamics of the Earth’s deep interior, isotopes in the environment, the crust and the solar system, rock magnetism, and paleobiology.
Computational Geoscience and Engineering
The Computational Geoscience and Engineering Section (CGE) is concerned with the prediction and monitoring of a wide variety of industrial and environmental processes, with a particular emphasis on the development and application of advanced numerical methods and scientific computing techniques.
The Computational Geoscience and Engineering team develops engineering solutions to some of the most pressing global problems: the supply of renewable energy, the sustainable production of metals and earth resources, and mitigating environmental impacts and risks. Application areas of interest include environmental engineering, renewable energy systems, coastal engineering, mining and mineral processing, natural hazards, nuclear engineering and pollution dispersal.
Petroleum Geoscience and Engineering Section
The Petroleum Geoscience and Engineering section conducts research into reservoir characterisation, subsurface fluid flow, and geophysics with application to oil and gas production and geological carbon sequestration. Areas of focus include fluid flow in porous media, reservoir simulation, reservoir characterisation, hydrocarbon thermodynamics, rock mechanics, time-lapse seismic, seismic inversion and imaging, and waveform tomography.