The 2016 Call To Prospective Students is extended for the four projects below, until 27th May, 2016 midnight
If you are interested in joining us in DREAM to study for a PhD in Big Data, Risk and Environmental Analytical methods, the 2016 call for projects has now been opened for applications, closing on Friday, 27th May, 2016 at midnight.
Background: The DREAM Centre for Doctoral Training will support three cohorts of 10 students, who will join the programme in October 2015, 2016 and 2017 respectively. We are now calling for applications for the second Cohort of Dream studentships (commencing October 2016). Two of the studentships in this forthcoming student intake will be interdisciplinary studentships co-funded by ESRC and NERC. These will focus on linking the social science research areas with environmental sciences research areas. The Doctoral studentships and topics we offer are advertised here and will also be disseminated across other routes.
The first cohort of Dream students are now well underway with their research projects, which are described here. All our positions are competitive and the student applications and interview stage allow us to identify and select the top applicants.
If you are interested in joining us in DREAM to study for a PhD in Big Data, Risk and Environmental Analytical methods, the 2016 call for projects is announced for student applications, together with a list of the prospective projects from which the 10 final selected projects to be run across the consortium universities will be drawn.
DREAM CDT Student Application Form »
Note, when completed, please email the form (plus additional documents as directed) to the respective university contact shown in the listings below.
|Newcastle University-based projects
For these projects, send completed applications to Dr Stuart Barr
|Multi-objective spatial risk and sustainability optimisation tools using cloud computing
Spatial risk assessment cannot be considered in isolation from other factors such as the development of long term sustainable plans for land use development and the implementation of planning decisions that mitigate adverse climate change impacts such as increased heat. To date however, the ability to develop spatial, multi-objective risk and sustainability planning tools has been limited by intractable computational run-times. Cloud computing now offers the potential to overcome this limitation, facilitating the development of spatial optimisation risk and sustainability planning tools that allow a large number of risk and sustainability objectives to be considered in the production of optimised spatial development plans.
In this PhD, cloud computing will be employed to provide the next generation of multi-objective, spatial risk and sustainability development plans for the UK. Using nationally available data-sets on climate related hazards, such as probabilistic predictions of heat, pluvial, fluvial and storm surge related flooding, along with future predictions of population demographics, the PhD will investigate how temporal spatial plans can be developed that minimise exposure to future spatial risk whilst maximising key local, regional and national sustainability objectives (e.g., minimising overcrowding, reducing urban sprawl, maximising access to low emission public transport etc.).
During the PhD, cloud computing training will be provided via a number of the Newcastle EPSRC CDT Big Data & Cloud Computing modules. The successful student will also have the opportunity to attend the two week NECSI Complex Systems modelling course in New England which previous PhD students at Newcastle have attended and found to be an excellent introduction to complex systems modelling and computing.
Reference: Caparros-Midwood, D., Barr, S.L., and Dawson, R., 2015. Optimized spatial planning to meet urban sustainability objectives. Computers, Environment and Urban Systems, 54, 154–164.
About you: Applicants should hold a minimum of a UK Honours degree at 2:1 level in a subject such as Engineering, Geomatics/GIS, Physical Geography or Environmental/Natural Science, Computer Science, Mathematics. Appropriate training will be provided, but capability in computer modelling and/or quantitative spatial analysis are desirable.
For further details: Please contact Dr Stuart Barr:
|Simulating the role of people in mediating environmental risks to infrastructure
This PhD will develop a new agent-based modelling approach to represent organisational and social interdependencies between infrastructure systems.
Analysis of infrastructure interdependencies has focused on the physical infrastructure networks, for example the supervisors have been looking at interdependent infrastructure systems and how failure of one physical system (e.g. energy network) can lead to knock on failure of other (e.g. loss of power to pump and distribute water supply), or vice versa (e.g. water is required for cooling power stations).
This work has highlighted some fascinating properties of interdependent networks – including how the nature of inter-connections can increase their overall vulnerability. However, decisions made by individuals and organisations who operate, manage and use these physical systems are just as important, if not moreso, in mediating interdependent interactions. To understand the role of these agents, will require a new approach able to capture and represent social systems. This PhD will develop a new coupled simulation model that combined an agent based model to represent interactions and decisions made about the operation of infrastructure, with simulation of the physical systems themselves. The sheer number of agents involved necessitates a cloud-based approach for large scale infrastructure simulation and so the developed approach must be computationally scaleable. The model will be tested on real infrastructure examples and used to identify strategies to improve the management and operation of infrastructure.
About you: Applicants should hold a minimum of degree at 2:1 level (or equivalent) in subjects such as Engineering, Computer Science, Geomatics, Mathematics, Physical Geography or Environmental/Natural Science. Appropriate training will be provided, but capability in computer modelling and/or quantitative spatial analysis are desirable.
For further details: Please contact Professor Richard Dawson:
|Environmental risks to resource lifelines such as water, food, fuel and materials
Extreme weather events, at a range of scales, have led to disruption of resource movements. These resources such as water, food, materials and goods are vital to the safety, health and livelihoods of individuals and communities. The 2011 Floods in in the Chao Praya River Basin in Thailand disrupted global computer manufacturing as about 25% of all hard drives in the world are manufactured in the region. Similarly, the 2011 East Coast of Japan tsunami reduced the production capacity of Japanese industry, with a slow of materials and supplies to downstream industries – including car assembly plants in the Northeast of England.
The scale of these global impacts is being driven by increasing interdependencies across infrastructures and supply chains. This complexity poses substantial challenges for those seeking to move resources, and environmental risk managers aiming to reduce the disruption to resource movements before, during and after extreme events.
This PhD will produce a quantitative resource model that simulates relationships of supply and demand of resources within a global scale spatial network model. The impacts of a spatial hazard, such as a flood, on these supply chains can be evaluated. The work builds on successful demonstration of this approach at the intra-urban scale and will take advantage of large data sets for supply chains, trade flows, environmental hazards as well as new computational capabilities to analyse large spatial networks.
The model will be used to provide an environmental risk assessment to global resource flows, identify priority supply chain and resource flow risks, and test the effectiveness of measures to increase their resilience.
About you: Applicants should hold a minimum of a UK Honours Degree at 2:1 level or equivalent in subjects such as Environmental Science, Computer Science, Engineering, Geography or Natural Sciences
For further details: Please contact Professor Richard Dawson:
|Birmingham University-based projects
For these projects, send completed applications to Dr Emmanouil Tranos
|Estimating the risk of Antarctic ice shelf collapse using Bayesian nonparametric statistical modelling.
Ice shelves comprise floating extensions of the inland ice of the East, West and Antarctic Peninsula ice sheets. They provide crucial buttressing forces holding back the flow of the ice sheets towards the sea, thus regulating rates of global sea-level rise. In recent years, ice shelves in the Antarctic Peninsula have been observed to substantially retreat and even catastrophically collapse. These major global change episodes have been linked to a variety of causal mechanisms, yet no single clear explanation has emerged, making physically-based forecasts of future change problematic.
This project will provide expertise and training in satellite remote sensing, expert elicitation, Bayesian methods and risk assessment to address the problem of ice shelf collapse. New satellite data (microwave and optical imagery) will be analysed to assess ice shelf retreat and collapse since 2010, placing these new observations in the context of the last half decade of observational ice shelf history. An expert elicitation exercise will quantitatively assess expert opinion of ice shelf collapse risk in the next 100 years.
These datasets will then be combined with existing environmental, geophysical and glaciological ‘Big Data’-sets in a Bayesian nonparametric statistical model framework to calculate the probabilities of ice shelf collapse risk during the next 100 years. The candidate will gain expertise and experience in glaciology, satellite remote sensing analysis, expert elicitation, and Bayesian numerical methods. This combination of skills is unique and in high demand and is expected to result in a number of high-impact outputs. The collapse timing estimates generated by this project may then be used by ice sheet modellers to more accurately forecast the future contributions of the Antarctic ice sheets to global sea-level rise.
About you: Candidates will normally hold relevant masters and first class or equivalent honours degrees in Physics, Mathematics, Computer Science, or numerate Geoscience disciplines (Geophysics, Earth Science, Physical Geography). Students with strong numerical and/or programming skills are particularly encouraged to apply.
For further details: Please contact Dr Nicholas Barrand:
Timeline and what happens next
- Extended studentship application closing date – Friday 27th May, 2016
- Notification of applicants selected for interview – Friday 3rd June, 2016
- Interviews held – by Friday 17th June, 2016
- Notification of successful applicants – Friday 1st July, 2016
- DREAM Cohort 2 induction programme, at Cranfield – October 2016