Fully-funded PhD position within the Department of Transport and Planning, Faculty of Civil Engineering and Geosciences, Delft University of technology, the Netherlands.
Closing date for applications: Nov 1, 2015
Understanding, estimating and predicting multi-modal mobility patterns is a complex task, since it involves predicting the result of decisions and interactions between millions of actors. For many years this task involved making a great many assumptions, which resulted in modelling approaches ranging widely from coarse equilibrium methods to highly detailed, activity-based methods.
In this project, part of the SETA H2020 EU project, the starting point is (huge amounts of really BIG) data from social media, GPS traces and much more, that make it possible to identify, estimate and calibrate highly detailed activity and choice models. These will be put to the test in three EU test-sites (Birmingham, Santander, Turin), to develop and improve new information services for both travellers and (public) transport operators, whereby mobility services can be improved and tailored to serve the needs of travellers at lower costs and higher performance levels. Using these unique data, your tasks are to explore, develop and evaluate prediction methods for both mobility demand and supply.
You will be supervised by Dr. Oded Cats and Prof. Van Lint and will work in the Delft integrated Traffic and Travel Laboratory (DiTTLAB.org) of the Transport and Planning Department. In this project you will closely cooperate with an international team of experts in this exciting, emerging field.
Requirements
You have a relevant MSc degree in transportation or a related field and a strong affinity for computer science. Alternatively, you have an MSc degree in computer science and a strong affinity for mobility. In either case, you have proven programming and data processing skills (in Matlab or e.g. Python, JAVA) and proven English communication skills, both in writing and orally.
How to apply
To apply, please e-mail a detailed CV, motivation letter and publication list. Make sure to include in your motivational letter (and/or CV) examples of projects in which you successfully demonstrate your programming and data processing skills. Please e-mail your application by 1 November 2011 to [log in to unmask]<mailto:[log in to unmask]> and [log in to unmask]<mailto:[log in to unmask]>. When applying for this position, please refer to vacancy number CITG15-35. For more information about this position, please contact Dr. Oded Cats, [log in to unmask]<mailto:[log in to unmask]>. See also the vacancy details on http://www.tudelft.nl/en/about-tu-delft/working-at-tu-delft/jobs/academic-jobs/
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