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  Machine learning for sustainable transportation systems


   Civil Engineering

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  Dr Muhammad Shafique  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

This is an interdisciplinary position at the intersection of artificial intelligence, deep learning, and transportation systems.

The research student will work on research projects focused on developing innovative machine-learning solutions for optimizing the integrated forecast models of electric vehicles for future smart cities.

This will include socioeconomic and other multiple factors such as modelling vehicle choices and placement of charging stations along with reinforcement learning for optimizing the choice of system parameters.

The project will also aim to forecast future electric vehicles' energy efficiency and performance assessment over the years by the combination of physical and deep learning models.

Qualifications

A successful candidate also has:

  • An excellent MSc degree in engineering, computer science, or a related field
  • Experience with applying data analytics and machine learning methods
  • Experience with deep learning algorithms, statistics, and learning theory
  • Strong programming experience in Python or similar language
  • Experience with physics-informed learning, graph neural networks (GNN), General regression neural network (GRNN), Recurrent Neural Network (RNN), Long Short Term Memory (LSTM) or physics-constrained generative neural network
  • Proven research-based publications in deep learning are a plus.
  • Excellent problem-solving skills.

Research journey

Doctoral research programmes (PhDs) take a proud place in the world-class research environment and community at Brunel. PhD students are recognised and valued by their supervisors as an essential part of their departments and a key component of the university's overall strategy to develop and deliver world-class research.

A PhD programme is expected to take 3 years full-time or 6 years part-time, with intakes starting in January, April or October.

The general University entrance requirement for registration for a research degree is normally a First or Upper Second Class Honours degree (1st or 2:1) or an international equivalent. A Masters degree is a welcome, but not required, qualification for entry.

Find out how to apply for a PhD at Brunel

Research support

Excellent research support and training

The Graduate School provides a range of personal, professional and career development opportunities. This includes workshops, online training, coaching and events, to enable you to enhance your professional profile, refine your skills, and plan your next career steps as part of the Researcher Development Programme. The researcher development programme (RDP) offers workshops and seminars in a range of areas including progression, research management, research dissemination, and careers and personal development. You will also be offered a number of online, self-study courses on BBL, including Research Integrity, Research Skills Toolkit, Research Methods in Literature Review and Principles of Research Methods.

Library services

Brunel's Library is open 24 hours a day, has 400,000 books and 250,000 ebooks, and an annual budget of almost £2m. Subject information Specialists train students in the latest technology, digital literacy, and digital dissemination of scholarly outputs. As well as the physical resources available in the Library, we also provide access to a wealth of electronic resources. These include databases, journals and e-books. Access to these resources has been bought by the Library through subscription and is limited to current staff and students. 

Dedicated research support staff provide guidance and training on open access, research data management, copyright and other research integrity issues.

Find out more: Brunel Library

Careers support

You will receive tailored careers support during your PhD and for up to three years after you complete your research at Brunel. We encourage you to actively engage in career planning and managing your personal development right from the start of your research, even (or perhaps especially) if you don't yet have a career path in mind. Our careers provision includes online information and advice, one-to-one consultations and a range of events and workshops. The Professional Development Centre runs a varied programme of careers events throughout the academic year. These include industry insight sessions, recruitment fairs, employer pop-ups and skills workshops.


Computer Science (8) Engineering (12) Mathematics (25)

References

Deep reinforcement learning in transportation research: A review
Machine learning for next-generation intelligent transportation systems: A survey

How good is research at Brunel University London in Engineering?


Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities
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 About the Project