We all know that global warming is a serious issue for the future of humankind and is intimately related with anthropogenic CO2 emissions. But what is the most critical process affecting atmospheric CO2 concentrations? In this project, you will be able to develop mathematical models to describe the process of the biological pump, which is deemed as the most critical process in regulating atmospheric CO2 concentrations and the global climate (Sigmann & Boyle 2000). Biological pump is the process that phytoplankton capture CO2 at sea surface (via photosynthesis) and transfer organic matters to the interior ocean by sinking. Due to the vast volume and the carbonate system, the deep ocean stores the majority of soluble inorganic carbon in the Earth system, thus playing the pivotal role in regulating atmospheric CO2. The exciting part of the project is that you will need to incorporate plankton functional diversity into the model, which has not been seriously considered in previous models.
It is anticipated that you will receive substantial trainings on mathematical and statistical modelling including but not limited to analyses on ordinary and partial differential equations and Bayesian inference. You will also have the invaluable opportunity to work on the high-performance computing system in Strathclyde (https://www.archie-west.ac.uk/
). Your mathematical, statistical, and programming skills are expected to be substantially enhanced during the PhD training. These skills will be very useful for securing some of the most popular jobs in this Big Data era.
You will mainly work within the Marine Population Modelling group, Department of Mathematics and Statistics, University of Strathclyde (https://www.strath.ac.uk/science/mathematicsstatistics/smart/marineresourcemodelling/
). You will also have the opportunity to collaborate with the group of Prof Hongbin Liu in Hong Kong University of Science and Technology.
Applicants should have or expect to obtain a good honours degree (1, 2.1, or equivalent) in applied mathematics, statistics, earth science, ecology, or a highly quantitative science. Experience of numerical modelling and programming in Fortran, Matlab or R would be highly beneficial, but not essential.
To apply, send 1) a complete CV, 2) a 1 page personal statement explaining your interests and skills for this project, and 3) names and contact information of three references to the lead supervisor, Dr Bingzhang Chen, Department of Mathematics and Statistics, University of Strathclyde, Glasgow at [email protected]
The preferred starting date is 30 September 2019.
We value diversity and welcome applications from all sections of the community.
The University currently holds a Bronze Athena SWAN award, recognising our commitment to advancing women’s careers in science, technology, engineering, maths and medicine (STEMM) employment in academia.
Sigman, D. M., & Boyle, E. A. (2000). Glacial/interglacial variations in atmospheric carbon dioxide. Nature, 407, 859.
Laws, E. A., Falkowski, P. G., Smith Jr, W. O., Ducklow, H., & McCarthy, J. J. (2000). Temperature effects on export production in the open ocean. Global Biogeochemical Cycles, 14, 1231-1246.
Cael, B.B. and Follows, M.J., 2016. On the temperature dependence of oceanic export efficiency. Geophysical Research Letters, 43, 5170-5175.
Chen, B. and Laws, E.A., 2017. Is there a difference of temperature sensitivity between marine phytoplankton and heterotrophs?. Limnology and Oceanography, 62, pp.806-817.