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Data mining for mixed methods energy data sets - dealing with uncertainty and calibrating the “human sensor”

  • Full or part time
  • Application Deadline
    Thursday, November 01, 2018
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

The project will look at the challenges and opportunities of inferring knowledge from and/or making decisions based on diverse datasets such as those obtained from energy systems and questionnaires.

There is a wide availability of low-cost wireless networkable sensors that can gather data about environments, human behaviours and interactions between people and common life objects. Dedicated networks can be built to collect detailed data over long periods of time. However, much of our understanding about human behaviour has come from surveys, interviews, focus groups and ethnographic studies. New methodologies that correctly analyse diverse, mixed datasets (sensor based and survey based) are critical to enhance our understanding of human behaviour, needs and aspirations, and drive decisions in response to a number of development challenges.

You will focus on Energy – one of the 17 Global Goals for sustainable Development ( – and will work within the EPSRC HELP-Refugee project, researching into understanding energy needs and providing new technical solutions for displaced populations in Rwanda and Nepal (

You will have access to energy survey data collected by the project team as well as data streamed from hundreds of wireless sensors embedded in deployed energy interventions (such as mobile lanterns, cookstoves, street lights and microgrids).

Working with an interdisciplinary team of scientists, your work will be supported by a number of project collaborators (Practical Action, NGO and Scene - a social IT enterprise pioneering solutions in the energy sector).

During the project, you will undertake field work, as well as taking up challenges that naturally come with interdisciplinarity. You will develop as a researcher, scientists and individual, through a structured learning programme that encourages you to use your strengths while gaining new skills. During your PhD, you are expected to make both theoretical contributions to the field as well as perform real-life evaluation of the innovations in scenarios offered by the HELP project.

Candidate Specification

• Entry criteria for applicants to PHD
A minimum of a 2:1 first degree in a relevant discipline/subject area with a minimum 60% mark in the Project element or equivalent with a minimum 60% overall module average.

In the event of a first degree classification of less than 2:1, a Masters Degree in a relevant subject area will be considered as an equivalent. The Masters must have been attained with overall marks at minimum merit level (60%). In addition, the dissertation or equivalent element in the Masters must also have been attained with a mark at minimum merit level (60%).
• a taught Masters degree in a relevant discipline, involving a dissertation of standard length written in English in the relevant subject area with a minimum of a merit profile: 60% overall module average and a minimum of a 60% dissertation mark
• the potential to engage in innovative research and to complete the PhD within a three-year period of study
• a minimum of English language proficiency (IELTS overall minimum score of 7.0 with a minimum of 6.5 in each component)

How to Apply

Apply on line
Submitting full supporting documentation, and covering letter, plus a 2000-word proposal addressing the research theme.

It is compulsory to contact Professor Elena Gaura with your covering letter, full CV and BSc and MSc transcripts before making a full application.

Interviews will be confirmed to shortlisted candidates.

Funding Notes

• £15000 bursary plus tuition fees - UK/EU/International
• For the academic year 2018/19, any English student who is not part of a research council can borrow up to £25,000 to help cover the cost of their PhD tuition fees. Further details can be found here: View Website

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