Coral reefs are the marine equivalent of rainforests: occupying 0.1% of the world’s ocean surface but hosting 38% of marine species. Reefs around the world are currently being destroyed by a number of factors, including rising ocean temperature. How will they react to predicted climate change?
We can use geological and biological knowledge, such as rock cores and changes in ecology through time, to predict the future. This project will create the first machine learning model of reef dynamics and incorporate both geological and biological data, enabling more accurate predictions of the impacts of future climate change.
We are looking for a student to join a growing and inclusive research team in York that uses numerical methods to tackle environmental problems. You should have a background in mathematics or computer science with a passion to develop geological and ecological knowledge or a background in geosciences/ecology with a keen interest in computer modelling. The project is truly interdisciplinary so we will provide specialist training as needed.
There is the possibility of travelling to the Great Barrier Reef to collect data to calibrate and test the model with partners at the University of Sydney within the project.
The research will be based in the Environment Department at the University of York. Rated second in the UK and 17th in the world for the impact of our research, the Environment department at the University of York offers an outstanding, dynamic and multidisciplinary environment in which to carry out PhD research. Our current PhD students come from many countries around the world and are well supported by a comprehensive programme of training and an inclusive supervision network.
For more information on supervisors see:
Relevant papers from the supervisors:
• Hill, J., Wood, R., Curtis, A., and Tetzlaff, D. M. 2012. Preservation of forcing signals in shallow water carbonate sediments. Sedimentary Geology 275-276: 79-92. DOI:10.1016/j.sedgeo.2012.07.017
• Hill, J., Tetzlaff, D.M., Curtis, A., and Wood, R. A. 2010. Modeling shallow water carbonates. Computers and Geoscience 35:1862-1874. DOI:10.1016/j.cageo.2008.12.006
• Parkinson, S.D., Funke, S.W., Hill, J., Piggott, M.D., Allison, P.A. 2017. Application of the adjoint approach to optimise the initial conditions of a turbidity current. Geoscientific Model Development 10, 1051-1068. DOI:10.5194/gmd-10-1051-2017
• Muto, T., Steel, R. J., & Burgess, P. M. (2016). Contributions to sequence stratigraphy from analogue and numerical experiments. Journal of the Geological Society, 173(5), 837-844. doi:10.1144/jgs2015-127
This is a 3.5 year fully-funded studentship part of the NERC Doctoral Training Partnership in Adapting to the Challenges of a Changing Environment (ACCE). The studentship covers: (i) a tax-free stipend at the standard Research Council rate (around £15,000 per year), (ii) tuition fees at UK/EU rate, (iii) research consumables and training necessary for the project.
Entry requirements: At least an upper second class honours degree, or equivalent in any relevant subject that provides the necessary skills, knowledge and experience for the DTP, including environmental, biological, chemical, mathematical, physical and social sciences.