We're hiring! Lecturer in Transport Modelling and Machine Learning
11 May 2019
The UCL Energy Institute’s MaaSLab focuses on urban transport and explores new mobility concepts, such as Mobility as a Service and mobility on demand, and new technologies such as automated vehicles, and drones. Its expertise lies on transport and behavioural models, survey design and innovative data collection techniques, big data handling and visualization, new mobility service design and business models.
We invite applications for a Lecturer in Transport Modelling and Machine Learning
The Lecturer will be a core member of MaaSLab, a team situated within the Energy and Transport Group of the UCL Energy Institute. The successful candidate will contribute to:
- The current research in transport models using machine learning techniques and expand it,
- The supervision of PhD students and teaching for the new MSc Program in Energy Systems and Data Analytics,
- The expansion of MaaSLab’s research portfolio by leading national and international grant applications,
- MaaSLab’s publication record,
- Managing and working for the research projects and daily operations of MaaSLab, and
- The enterprise activity of MaaSLab.
This is a open-ended position without a funding end date.
See full details and apply via UCL Jobs
The successful candidate shall hold a PhD or be near to completion, or have commensurate research experience in computer science, transport, software engineering, data science, mathematics, geoinformatics or related fields. She/He shall have skills in developing transport models using machine learning (e.g. transport simulation models, dynamic travel behaviour modelling for new on-demand mobility services, traffic simulation, econometric modelling, machine learning applications for transport demand prediction etc.). The candidate shall also have excellent knowledge of a programming language (i.e. Python, C++, MATLAB, R etc.) and evidence of accessing and handling different types of quantitative data (e.g. geolocation, timeseries, mobile phone data, travel patterns etc.).
If you have any queries regarding the vacancy or the application process, please contact: email@example.com
UCL Taking Action for Equality
We will consider applications to work on a part-time, flexible and job share basis wherever possible.
- 9 Jun 2019
This appointment is subject to UCL Terms and Conditions of Service for Academic Staff.