The 2016 Call To Prospective Students is extended for the two projects below, until 31st August, 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 is open for the two applications below, closing on Friday, 31st August, 2016 at midnight.
Background: Overall, 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 calling for applications for the second Cohort of Dream studentships (commencing October 2016). Two positions remain open. Two of the studentships we have now allocated for 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.
|Birmingham University-based projects
For these projects, send completed applications to Dr Emmanouil Tranos
|Predicting hydrological drought risk in Europe using big data of socio-economic and natural factors
Drought is one of the costliest natural hazards in Europe and drought risk is expected to increase in the future. To improve hydrological drought risk prediction both natural and socio-economic factors need to be taken into account. Socio-economic factors determine the vulnerability to drought and natural factors determine the link with the drivers of drought. In both categories various data sets are available, from different sources (satellite data, ground observations), on different scales (local to pan-European), in different formats (written impact reports, point data, gridded data), that need to be combined in a clever way to improve hydrological drought risk prediction (see Figure). This project aims to develop new statistical tools to contribute to improved drought prediction on European scale. Results of this project will feed into the European Drought Observatory (EDO; edo.jrc.ec.europa.eu/), which provides real-time drought information, but currently lacks hydrological drought risk maps. The objectives of this project are:
For this project, we want to explore the usability of a number of novel data sources, for example NASA’s Gravity Recovery and Climate Experiment (GRACE; grace.jpl.nasa.gov/) satellite product that measures total water storage, and the new European Drought Impact report Inventory (EDII; www.geo.uio.no/edc/droughtdb) that consolidates qualitative information on the impacts of historical European drought events for a large range of sectors.
About you: Applicants should hold a minimum of a UK Honours Degree at 2:1 level or equivalent in subjects such as Geography, Disaster risk management, Water management / hydrology, Meteorology / climatology, Engineering, or Natural Sciences. Furthermore, applicants are expected to show evidence of proficiency in handling large data sets, programming and mathematical skills.
For further details: Please contact Dr Anne F. Van Loon:
|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 9th September, 2016
- Notification of applicants selected for interview – by Monday 12th September, 2016
- Interviews held – by Friday 16th September, 2016
- Notification of successful applicants – Monday 19th September, 2016
- DREAM Cohort 2 induction programme, at Cranfield – October 2016