About the award
Location:Â Â Cornwall Campus, University of Exeter.
Primary Supervisor:Â Dr Markus Mueller, University of Exeter.
Recent work at the University of Exeter has contributed deep insight into the comparative demography of plants and animals, particularly the potential for transient dynamics to buffer populations and life histories against environmental disturbances and perturbations. Age-structuring of life histories provides natural resilience against mass mortality events. Life histories can evolve to buffer their most important rates of survival and reproduction against the damaging effects of environmental fluctuations.
We have access to a rich source of demographic data for hundreds of human populations around the world. We aim to:
(i) Ask whether human demographies are naturally resilient to the âtypicalâ demographic disturbances suffered by those populations. For example, we might expect populations suffering regular disease outbreaks to have earlier onset of reproduction in order to replace lost youth.
(ii) Ask whether human life histories are buffered against environmental heterogeneity. The key predictions here are that age-specific rates of reproduction or mortality that have most influence on population growth rate (measured by the ranked sensitivity of lambda, the dominant eigenvalue of the human Leslie matrix, to each vital rate), will be those with lowest variance among years.Â
(iii) Project various scenarios of social change (e.g. National Health Services, Pension Schemes, Immigration Policies) into naÃ¯ve national demographies, based on evidence of demographic impacts from nations that already practice them. Ask whether nations vary in their âfitnessâ to social and environmental changes and trade-off economic and social impacts of âtranslocated demographyâ.
The PhD project is a classic piece of Applied Mathematics, focused on the very real and global issues of ageing populations and environmental change. Our goal is to use BIG data to understand the complexity of human demography at regional, national and global scales. This understanding will help to forecast demographies into uncertain future environmental, political and social scenarios.
We will make use of and, if necessary, develop new mathematical tools to process and analyse BIG data. The analysis will leverage the mathematical modelling of complex dynamical systems which are able to make robust predictions under uncertain external impacts.
You will be based in the Environment and Sustainability Institute (ESI) at the University of Exeterâs Penryn Campus and will be expected to collaborate with researchers within the ESI, the University of Exeterâs Centre for Ecology and Conservation, the University of Exeterâs European Centre for the Environment and Human Health, and partners from governments and NGOs on various aspects of the project.
For informal enquiries contact:Â firstname.lastname@example.org
You should have or expect to achieve at least a 2:1 Honours degree, or equivalent, in Mathematic, Computer Sciences or Natural Sciences. Experience in mathematical modelling, numerical modelling, signal processing, and with tools such as MatLab and R or other mathematical modelling tools are highly desirable though not essential.
Application deadline: 13th October 2013
Number of awards: 1
Value: EPSRC funded 3.5 year studentship, Tuition fees (UK ) and Â£13,726 annual maintenance allowance at current research council rate
Duration of award: per year
Contact: Liz Robertsempsemail@example.com
How to apply
To apply, you must complete theÂ online web form. You will be asked to submit some personal details and upload a full CV, covering letter and details of two academic referees. Your covering letter should outline your academic interests, prior research experience and reasons for wishing to undertake this project.
For general enquiries please contact Liz Roberts atÂ firstname.lastname@example.org