Applicants must be able to demonstrate based on their previous experience the capability to undertake the analysis required for this project.
Proficiency in Python is essential
experience of using machine learning techniques would be desirable
Familiarity with TensorFlow (or similar), knowledge of railway systems in Europe and the ability to read paper railway timetables would all be an advantage but are not essential.
Applicants require a minimum of a good 2:1 degree at undergraduate level in a relevant subject area.

The availability of historical time series data on transport service provision is crucial for research into a range of topics. However, data for the majority of the period when public transport services have operated is only available in paper timetables or (at best) scanned image files. This PhD project will develop automated methods for converting scanned image files of historic timetable data into machine readable formats suitable for mapping and quantitative analysis, such as GTFS (General Transit Feed Specification) files. The analysis will be based on a case study of overnight trains in Europe. A fully funded studentship is available for UK applicants covering fees and stipend. Location: Birmingham.

PhD in Relevant Subject Area

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