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PhD Studentship: Towards an Intelligent Hybrid Energy and Transportation System in the Presence of Large-Scale EVs and Renewable Energy

University of Essex - Department of Mathematical Sciences (in collaboration with School of Computer Science and Electronic Engineering)

Qualification Type: PhD
Location: Essex
Funding for: UK Students, EU Students
Funding amount: See advert text.
Hours: Full Time
Placed On: 13th February 2020
Closes: 31st March 2020

Funding: A full Home/EU fee waiver or equivalent fee discount for overseas students  (£5,103 in 2020-21) (further fee details - international students will need to pay the balance of their fees) plus a doctoral stipend equivalent to the RCUK Minimum Doctoral Stipend (£15,009 in 2019-20, stipend for 2020-21 tbc).

Application deadline: Tuesday 31 March 2020

Start date: October 2020

Duration: 3 years (full time)

Location: Colchester Campus

Based in: Department of Mathematical Sciences (in collaboration with School of Computer Science and Electronic Engineering)

Overview

Increasing efforts have been made in large-scale integration of electric vehicles and renewable energy to reduce the greenhouse emissions in transport and energy sectors in order to achieve a net zero emissions society for the UK.

However, the large-scale uptake of EVs and renewable energy brings new constraints, challenges and mutual effects to operations of existing energy and transportation systems and will create a coupled hybrid system exhibiting complex interactive behaviours among different parties with a series of challenging and open research problems to be answered.

The project

This project aims to develop an intelligent hybrid energy and transportation system in the presence of large-scale EVs and renewable energy with the-state-of-the-art game-theoretic and agent-based decision making, stochastic optimisation and deep learning methods.

The successful candidate will receive supervisions from experts in both Department of Mathematical Sciences and School of Computer Science and Electronic Engineering.

During the project, the candidate will have the opportunity to visit external research organisations and build contacts with industry.

Supervisors

Dr Fanlin Meng – Lead Supervisor

Professor Dongbing Gu – Co-Supervisor

Dr Xinan Yang – Co-Supervisor

Criteria

BSc (1st) in Data Science, Computer Science, Maths or other relevant subjects with significant maths and computer science components.

An MSc in relevant subjects is an advantage but not compulsory.

How to apply

You can apply for this postgraduate research opportunity online.

Please include your CV, covering letter, personal statement, and transcripts of UG and Masters degrees in your application.

The University has moved to requiring only one reference for PhD applications and these can be received after a conditional offer has been made so the absence of these will not hold up the recruitment process.

Find out more about this studentship and information on how to apply on our website.

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