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Bayesian Statistical Modelling for Quantitative Risk Analysis

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  • Full or part time
    Dr FK Lindgren
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

University of Bath / DNV GL – PhD studentship available - Deadline for applications: Wednesday 8th April 2015

Bayesian Statistical Modelling for Quantitative Risk Analysis

In collaboration with the EPSRC Centre for Doctoral Training in Statistical Applied Mathematics at Bath (SAMBa) www.bath.ac.uk/samba

The Department of Mathematical Sciences at the University of Bath and DNV GL, a company who use statistical models to provide risk assessments across a wide range of industries have developed a PhD project which will be co-funded for 3.5 years starting in September 2015.

We are looking for exceptionally qualified students wanting to work at the interface between applied mathematics, statistics, and probability, with a clear industrial focus.

Brief project description: Quantitative Risk Analysis (QRA) has been applied to risk and safety assessment for major accidents in the oil and gas industry. The interaction between system components can be handled by directed network graphs of probabilistic and deterministic sub-models, leading to a computationally challenging problem that requires novel solution techniques. Advances in Bayesian
statistical modelling, estimation, and computational methodology should be exploited to advance the state of the art of practical QRA, and to analyse model sensitivity and uncertainty. The aim of the PhD would be to develop innovative QRA models, e.g. including human factors and temporal dynamics, and computational methods for larger and more realistic models than current techniques allow.

Candidates should have a strong background in mathematical statistics, including statistical modelling, strong probability or Markov processes. Programming, numerical methods and simulation skills are also essential.

The supervisory team will be drawn from a number of potential supervisors at DNV GL and Bath, including Dr David Worthington (DNV GL), and Dr Finn Lindgren, Dr Simon Shaw, Dr Evangelos Evangelou and Dr Karim Anaya-Izquierdo (Bath). Students will be based in Bath but expected to spend time on placements at DNV GL’s offices.

Students taking up the award will benefit fully from the infrastructure of Bath’s EPSRC Centre for Doctoral Training (SAMBa). This includes symposia seminars delivered across a wide range of topics in mathematics, statistics, and their applications, week-long Integrative Think Tanks involving industry, academics and students formulating mathematical problems, transferable skills training and support to attend academic conferences.

Further information about the Department of Mathematical Sciences, and the EPSRC CDT in Statistical Applied Mathematics is available on www.bath.ac.uk/samba.

Funding Notes

The University of Bath's Department of Mathematical Sciences and DNV GL, a company who use statistical models to provide risk assessments across a wide range of industries have developed a PhD project which will be co-funded for 3.5 years starting in September 2015.

We are looking for exceptionally qualified students wanting to work at the interface between applied mathematics, statistics, and probability, with a clear industrial focus.

Funding includes full tuition fees at the home rate, a training support fee of £1,000/annum and tax-free maintenance of £14,057/annum (2015/16 rate). Only UK and EU students are eligible for this funding.

References

Expressions of interest should be sent to the SAMBa Centre Manager, Dr Susie Douglas, via email ([email protected]) and should include:
- A short statement (250 words) explaining your motivation for applying
- A 2-page CV which includes your academic and work experience, your nationality and country of normal residence (for the past 3 years, not including full time education)
- Scans of your academic transcript(s)
- Information on where you heard about the studentship

All applications will be reviewed rapidly and promising applicants will be invited to an interview.

How good is research at University of Bath in Mathematical Sciences?

FTE Category A staff submitted: 44.40

Research output data provided by the Research Excellence Framework (REF)

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