About the Project
You will explore the potential of emerging computational approaches to transform our ability to image the Earth’s subsurface and quantify the model uncertainty. We envisage a new generation geophysical simulator, that may be based on machine learning approaches, allowing us to study the Earth’s dynamic subsurface at a scale that is an order of magnitude above what we can presently do. Once developed, you will test the new approach on rich datasets such as those obtained from monitoring landslides and earth dams.
You will work within a team from the Lancaster Environment Centre (LEC), British Geological Survey (BGS), UK Centre for Ecology & Hydrology (UKCEH) and Nottingham University, with CASE industrial partner Socotec. You will have access to state-of-the-art measurement systems (and their data) along with existing software used to analyse such data.
Applicants should hold a minimum of a UK Honours Degree at 2:1 level or equivalent. They should have studied to degree level subjects such as Computer Science, Applied Mathematics, Computational Physics, Engineering, or Earth Science with strong numerical elements.
For further details please contact Prof Andrew Binley ([Email Address Removed]).
For more detailed eligibility criteria please see the Envision website - http://www.envision-dtp.org/projects/information/.
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