PhD Studentship in Computational approaches to Uncertainty in Scenario-based models of Climate Change Impacts at Heriot-Watt University


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PhD Studentship in Computational approaches to Uncertainty in Scenario-based models of Climate Change Impacts at Heriot-Watt University


PhD Studentship in Computational approaches to Uncertainty in Scenario-based models of Climate Change Impacts at Heriot-Watt University

Overview
Heriot-Watt University – Computer Sciences Department Applicants are invited for a fully funded PhD studentship on “Computational approaches to Uncertainty in Scenario-based models of Climate Change Impacts” at the Computer Sciences Department at Heriot-Watt University, Edinburgh (joint supervision with Centre for Climate Change and Sustainability at Edinburgh University). For further information please contact Oliver Lemon ([email protected] ).

Closing date for applicants: 15 August 2010
Starting: October 2011 (negotiable)
Length: 4 years

The aim of this studentship is to develop new computational models to assess uncertainties in the prediction of climate change impacts and explore alternative policy response strategies to better mitigate climate vulnerability. It will formally identify and quantify sources of uncertainty and explore probabilistic methods (e.g. Probabilistic Graphical Models) which capture distributions over possible futures and allow efficient inference over hidden (unobservable) variables.

This project is highly inter-disciplinary and will bring together expertise in “scenario-based” simulations of climate change and probabilistic modelling of interactions under uncertainty.

It will be jointly supervised by Oliver Lemon (Department of Computer Science, Heriot-Watt University) and Mark Rounsevell (Centre for Climate Change and Sustainability, Edinburgh University). If successful, the degree will be awarded by Heriot-Watt University.

Eligibility
Candidates should have a First Class Honours or a good Master`s degree in Computer Science or Mathematics and have excellent programming skills. Experience with probabilistic modelling techniques and statistics is essential, and knowledge of machine learning and agent-based modelling is highly desirable. A background in climate change, ecology and scenario-based modelling would also be desirable, but is not strictly necessary.

The stipend will cover all study fees and a living stipend for 4 years. The project will also provide travel funds for the student to attend international conferences.

Further information
For further information please contact Oliver Lemon ([email protected] ) and Verena Rieser ([email protected] ).

For your application please send:

  • a supporting statement (1 page)
  • a Curriculum Vitae (CV)
  • English language certificates (for EU and Overseas applicants)
  • contact details for academic references.

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