Dear friends and colleagues,
Apologies for cross-posting, please forward this 4 year PhD opportunity to potentially interested candidates …
“How complex should a land surface model be to accurately predict extremes?”
We live in a data-rich world, yet the representations of the land surface in climate models were largely conceived in the absence of observations. Comparisons against observations identify model weaknesses; this then fuels a drive towards increased model complexity. How much of this added complexity is warranted? This project aims to build the simplest model of the terrestrial biosphere that the data can support. The project will combine a data-driven approach with the principles of optimality theory. By delivering a simpler, data- and theory-driven model we will unlock new understanding about climate model behaviour to improve predictions of climate extremes.
The student will receive a stipend of 40K per year for four years, as well as up to $10k each year for career development. The project is based at the Climate Change Research Centre at the University of New South Wales (UNSW), Australia, under the supervision of Dr Martin De Kauwe, Professor Andrew Pitman and Associate Professor Lisa Alexander. Both international and domestic applications are strongly encouraged.
The successful candidate will be aligned with the Australian Research Council Centre of Excellence for Climate Extremes an international research consortium of five Australian universities (The University of New South Wales, Monash University, The University of Melbourne, The University of Tasmania and The Australian National University) and a suite of outstanding national and international Partner Organizations. The Centre provides excellent opportunities for travel and graduate student development.
We are looking for expressions of interest from outstanding graduates with a strong academic record including Honours Class I or equivalent. Graduates with a strong background in mathematics, physics, atmospheric science, engineering or a similar quantitative science are particularly encouraged to apply. Programming experience with C, Fortran 90, Python or R is highly desirable.
Questions should be directed to Martin De Kauwe (firstname.lastname@example.org) – the application process is a little involved and we will guide suitable applicants through it. Further details about the Scientia PhD scholarships can be found at https://www.2025.unsw.edu.au/apply and summarised in the FAQ (https://ift.tt/2L3raSx).