MPhil/PhD Studentship in Intelligent transportation

Investing in excellence: studentship opportunities

The University of Derby has an opportunity for a full-time postgraduate research studentship in the Data Science area of research.

Qualification type: Location: Funding amount: Hours: Closes: Interview: Start date:
MPhil/PhD Derby, UK £17,668 stipend pa + UK home tuition fees Full-time Midday on 6 January 2023 23 January - 1 February 2023 June 2023

The successful applicant will receive a maintenance stipend (based on the minimum stipend defined by UKRI, currently £17,668 for the academic year 2022/23) and home MPhil/PhD tuition fees only up to the target submission date.

Please note, if your application is successful and you are assessed as Overseas for fees purposes, you will need to pay the difference between the Home fees and the EU/Overseas fees.

The intended intake period is June 2023, or the next available intake. 

The successful applicant will be expected to complete their MPhil/PhD within 3 years on the MPhil/PhD route, contribute to the College of Science and Engineering REF submission and get involved in the wider research activities of the College. 

Applicants will become part of a friendly and welcoming team and will be supported and managed by their supervisors. 

The vacancy details are as follows: 

Purpose/objectives 

In major cities, traffic congestion has a negative impact on travel time, pollution and citizens' health. This is the main issue for passengers, drivers, infrastructure managers, traffic controllers and management, to select short, fast and environmentally friendly paths and recognize unexpected traffic conditions.

The research will specifically address technical challenges in continuous performance improvements of deep learning neural networks of suitable architectures to support traffic management using Natural Language Processing and visualisation techniques.

Project description 

The project aims at developing a digital platform to support intelligent transportation systems (ITS) using data that is available and mainly created by transport systems users from social networks, and other platforms and agencies. The platform will examine transport services, support traffic control and management, and solve traffic-related problems. On the other hand, the analysis of these data can aid travellers to identify risky zones, save time and fuel consumption and increase the safety of their journeys. 

The research will specifically address technical challenges in continuous performance improvements of deep learning neural networks of suitable architectures to support traffic management using Natural Language Processing and visualisation techniques. 

The ideal candidates should have an excellent grasp of modern machine learning and deep learning models and possess good skills in fast prototyping of new solutions and other aspects of research. Previous programming experience, in python and/or R and visualisation techniques, is required. A very good BSc or preferably an MSc degree in computer science or AI/data science is required. Excellent communication skills are essential for the candidates to communicate effectively with the research team and stakeholders.

Potential project impact 

The platform has the potential to attract users, organisations and agencies interested in intelligent transportation systems, especially since most cities are now moving to data-driven decision-making. It is expected that high-quality publications will be produced as part of this studentship and benefit the university's REF submission.

Principal accountabilities and responsibilities

The successful applicant is expected to:

To apply 

Completed applications should be submitted via our online application system quoting funding reference:  S&E_Data Science_1122

For other enquiries which are subject-specific please contact Professor Farid Meziane (f.meziane@derby.ac.uk). 

Closing dates for applications: Midday on 6 January 2023 

Interviews: 23 January - 1 February 2023

If you have not been invited for an interview by the interview date, please assume your application has been unsuccessful.  

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