Research Fellow in Machine Learning and Spatial Statistics, Warwick, UK

Research Fellow in Machine Learning and Spatial Statistics, Warwick, UK

Jan 16, 2018

University of Warwick; joint post between the Departments of Computer Science and Statistics.

Fixed-term contract for 24 months. The start date to be agreed with the successful candidate. Salary £29,799 – £38,833 per annum.

We are seeking to recruit a postdoctoral research fellow to work in the area of machine learning and spatial statistics.

You will be expected to perform high quality research under the supervision of Dr. Theo Damoulas and Prof. Mark Steel, as part of the Turing-Lloyds Register Foundation funded project ‘Air Quality Sensor Networks’. This project is likely to involve hierarchical Bayesian models, nonparametric Bayesian inference, graphical models, active learning, experimental design and issues in spatio-temporal inference such as non-stationarity and non-separability. The expectation is that you will produce breakthrough research results in the areas of sensor placement, high-resolution space-time forecasting, dynamic modelling, and contribute to publishing these results in top rated venues.

You will possess a PhD or an equivalent qualification in Statistics or Computer Science or Applied Mathematics (or you will shortly be obtaining it). You should have a strong background in one or more of the following areas: Bayesian inference, spatial statistics, probabilistic machine learning.

The post is based in the Departments of Statistics and Computer Science (joint appointment) at the University of Warwick, but the work will be conducted in close collaboration with the Alan Turing Institute. You will frequently travel to Turing to participate in meetings and present your work with the opportunity to spend considerable periods of time visiting and working in the institute. You will join a team of researchers affiliated with the ATI and led by Dr Theo Damoulas, including research assistants and PhD students in statistics and computer science.

Candidates should provide their application form a CV, a list of publications and a research statement.

More details and an application form can be found at

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