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Senior Research Associate Position in Environmental Data Science: Learning and Optimisation

Mathematics & Statistics
Salary:   £33,518 to £38,832
Closing Date:   Sunday 18 March 2018
Interview Date:   Wednesday 18 April 2018
Reference:  A2212

Four post-doctoral research positions, each of four years, are available in an exciting, cross-disciplinary programme of research to develop and deploy a data science of the natural environment (http://www.lancaster.ac.uk/dsne). The project comprises data scientists, environmental scientists and a range of stakeholders, and will focus on methodological innovation in data science to tackle grand challenges around environmental change. This work is funded by the EPSRC under their New Approaches to Data Science call (https://www.epsrc.ac.uk/funding/calls/newapproachestodatascience). This is a prestigious and high profile award targeting a paradigm shift in the role of data in environmental science and in associated decision making. 

The research programme focuses on integrating spatio-temporal statistical models and extreme value methods, with Gaussian process emulation of deterministic and stochastic environmental process models, and Bayesian optimisation and other machine learning methods leading through to decision support. All methodology will be deployed in a newly developed and open source virtual lab environment.  You will develop novel approaches that address the particular data science demands in terms of understanding and managing the natural environment. The research will be driven by selected environmental grand challenges in the areas of ice sheet melt prediction, air quality modelling and land use management.

This particular position focuses on the development of machine learning approaches for learning in environmental data science. You will develop methods related to Bayesian optimisation and active learning, and apply them in the context of environmental models to facilitate decision-making by both environmental scientists and policy makers. Experience of working with environmental data would be an advantage but not essential.

We are particularly interested in applicants who are excited by working on environmental grand challenges and on the potential of working at the interface between disciplines in addressing these challenges. The research will be varied and exciting, with the potential to shape an emerging field of real importance.

A PhD or equivalent degree in statistics (or a closely-related field) is required to be eligible for this position.  You will have a track record of high-quality publications in areas of relevance to the project and the willingness to undertake ambitious and challenging research.  For more details, please see the detailed Job Description/Person Specification for this position.

This position is being advertised together with three other research positions in data science 

A2211 Senior Research Associate Position in Environmental Data Science: Virtual Labs in the Cloud
A2213 Senior Research Associate Position in Environmental Data Science: Integrated statistical modelling
A2214 Senior Research Associate Position in Environmental Data Science: Spatio-temporal extremes

All positions are available for up to 48 months and are available to start from 1st April 2018.

Interested candidates are strongly encouraged to contact Prof. David Leslie in advance of making an application (d.leslie@lancaster.ac.uk).

We welcome applications from people in all diversity groups, and are keen to discuss job share opportunities with interested candidates.

The closing date for this job opportunity has now passed, and applications are no longer being accepted for this position

Further details:

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