Project funded through the E4 DTP based in Edinburgh: View Website
Find more information on the application process here: View Website
A background in statistics, data science, ecological and/or environmental science, or related biological discipline is favoured, but transfers from physical sciences are possible. Strong quantitative skills are vital, and experience or interest in data analytics would be helpful. An interest in ecological and environmental issues would be advantageous.
Smallman, T.L. and Williams, M., 2019. Description and validation of an intermediate complexity model for ecosystem photosynthesis and evapotranspiration: ACM-GPP-ETv1. Geoscientific Model Development, 12(6), pp.2227-2253.
O’Hagan, A., 2006. Bayesian analysis of computer code outputs: A tutorial. Reliability Engineering & System Safety, 91(10-11), pp.1290-1300.
Cumming, J.A. and Goldstein, M., 2010. Bayes linear uncertainty analysis for oil reservoirs based on multiscale computer experiments. O’Hagan, West, AM (eds.) The Oxford Handbook of Applied Bayesian Analysis, pp.241-270.
FTE Category A staff submitted: 56.80
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