Developing Diffusion Models for Electric Vehicle: Spatial-temporal analysis and Policy Evaluation PhD 36 months PHD Programme By Loughborough University |TopUniversities

Programme overview

Degree

PhD

Study Level

PHD

Study Mode

On Campus

Developing Diffusion Models for Electric Vehicle: Spatial-temporal analysis and Policy Evaluation PhD
The widespread uptake of Electric Vehicles represents the primary means through which deep cuts in greenhouse gas emissions from the transport sector will be achieved. Charting this spread and determining what factors influence its speed is essential for managing this mitigation strategy and for creating a low-carbon mobility system.
This project taps into this important societal objective and focuses on the development of models that reveal the underlying mechanisms that steer the transition to Electric Vehicles. Key tasks in the project are:
  • Chart this historic spatial-temporal diffusion of EVs across the UK
  • Create diffusion models that forecast this uptake out to 2050
  • Produce policy scenarios that can affect this diffusion

Programme overview

Degree

PhD

Study Level

PHD

Study Mode

On Campus

Developing Diffusion Models for Electric Vehicle: Spatial-temporal analysis and Policy Evaluation PhD
The widespread uptake of Electric Vehicles represents the primary means through which deep cuts in greenhouse gas emissions from the transport sector will be achieved. Charting this spread and determining what factors influence its speed is essential for managing this mitigation strategy and for creating a low-carbon mobility system.
This project taps into this important societal objective and focuses on the development of models that reveal the underlying mechanisms that steer the transition to Electric Vehicles. Key tasks in the project are:
  • Chart this historic spatial-temporal diffusion of EVs across the UK
  • Create diffusion models that forecast this uptake out to 2050
  • Produce policy scenarios that can affect this diffusion

Admission Requirements

3.2+
6.5+
92+
Applicants should have, or expect to achieve, at least a 2:1 honours degree (or equivalent) in a relevant subject such as geography, economics, or engineering. A relevant master’s degree and/or experience is desirable. 
The ideal candidate for this project will be quantitatively minded and have experience in specifying multivariate models. Awareness of econometrics, spatial analysis, geo-computation, and/or optimisation modelling would be advantageous.

01 May 2025
3 Years
Jan
Jul

International
27,500

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