29 January 2018
Lancaster University is advertising three fully-funded PhD positions in the Centre of Excellence in Environmental Data Science, a joint venture between Lancaster University and the NERC Centre for Ecology & Hydrology (CEH). We have recently been awarded a large grant to develop a Data Science of the Natural Environment. As a PhD student, you will be at the heart of this project, benefitting from participating in a large cross-disciplinary team of scientists and all the excitement surrounding that.

You will be part of a multi-year project to develop a Data Science of the Natural Environment, bringing together researchers from CEH, the Lancaster Environment Centre (LEC) and Lancaster’s Data Science Institute to develop and deploy modern machine learning and statistical techniques to enable better-informed decision-making as our climate changes.

While an explosion in data science research has fuelled enormous advances in areas as diverse as eCommerce and marketing, smart cities, logistics and transport, health and wellbeing, these tools have yet to be fully deployed in one of the most pressing problems facing humanity, that of mitigating and adapting to global change. This project brings together world-leading statisticians, computer scientists and environmental scientists alongside an extensive array of key public and private stakeholder organisations to effect a step change in data culture in the environmental sciences.

The project will develop a new approach to data science of the natural environment driven by three representative grand challenges of environmental science: predicting ice sheet melt, modelling and mitigating poor air quality, and managing land use for maximal societal benefit.

The three advertised PhD topics are on these three challenge areas. In each, there is already an extensive scientific expertise, with intricate models of processes at multiple scales. However this sophisticated modelling of system components is usually let down by naive integration of these components together, and inadequate calibration to observed data. The consequence is poor predictions with a high level of uncertainty and hence poorly-informed policy making.

By building a team that spans the inter-disciplinary divisions between data and environmental scientists we can ensure the necessary interoperability of methods that is currently lacking. Working with a large range of stakeholder environmental organisations will enable a culture shift in the data literacy of the environmental sciences to enable better decision-making as climate change places ever greater strains on our society.

For more information on the projects and the application process, please see the project descriptions. The deadline for applications is 1:00pm Friday 16 February 2018 and due to the limited time between the closing date and the interview date, it is essential that you ensure references are submitted by the closing date.