Fully funded PhD studentship in Machine Learning for Analyzing and Predicting Climate Change at Ghent University --- Duration of studentship: 4 years Studentship start date: October 2014 Application closing date: July 15th (will be extended if no suitable candidate is found). --- Background information: Recent advances in satellite Earth observation – with the development of consistent global historical records of crucial environmental and climatic variables – provide new means to start unravelling the processes driving long-term changes in climate extremes, and understanding the impact of these changes on terrestrial ecosystems. In addition, these datasets offer an observational benchmark to evaluate the skill of climate models at representing climatic extremes and vegetation dynamics. Project description: For the project SAT-EX, which is funded by the Belgian government and which starts in the fall, we are currently looking for three PhD students and one postdoctoral researcher. One of the PhD studentships is available in the field of "Machine Learning for Analyzing and Detecting Climate Change" under supervision of Willem Waegeman, in the research unit Knowledge-Based Systems of Ghent University. See www.sat-ex.ugent.be for details. SAT–EX raises with the goals of revealing how droughts, heatwaves and extreme rain events have changed in frequency and intensity over the past three decades, to uncover the causes behind these changes and the consequences for terrestrial vegetation. The ability of our current IPCC climate models to estimate these processes will be evaluated by comparison to novel satellite-based data records. In the long run, SAT–EX findings will advance towards the timely forecasting of climate extremes, provide valuable insights about the management of water resources during extreme events, help characterize global terrestrial carbon budgets, and reduce the uncertainty in long-term model predictions of climate extremes and global vegetation dynamics. The ideal candidate for the position has the following profile: - An MSc degree in (Bio-)Engineering, Computer Science, Physics, Mathematics, Statistics, or equivalent – candidates from outside Belgium are welcome, but they are expected to move to Ghent for four years - An interest in fundamental machine learning research, as well as practical applications in hydrology - Experience with at least one programming language (Matlab, R, Python, Java, etc.) - An interest for data management and data analysis in general - Good knowledge of machine learning and/or statistical methods is a strong asset - Fluent in English (speaking and writing) - Team player with good communication skills How to apply Send your c.v. and a short email with a one-paragraph motivation to Willem Waegeman (firstname.surname@ugent.be)
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