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Information about Research Studentship in Energy Data Privacy

Research Studentship in Energy Data Privacy

3.5-year D.Phil. studentship 

Project: CREDS (Center for Research in Energy Demand Solutions)

Supervisors: Dr Phil Grunewald

This studentship will systematically research the privacy implications of smart meter data from a social and a technical perspective. Smart meter data is rightly considered sensitive. Even anonymised data can contain potentially discriminating features, such as religion (e.g. changes in use patterns during Ramadan or other festivities). Heating patterns can reveal under served heating needs, which could result in respiratory ill health. Such data can be used for good, to target retrofit measures, but it could equally be used by health insurance companies to disadvantage already fuel poor households.

Nuanced considerations of a social and a technical nature need to be weighed up to inform policies on the handling and access to energy related data.

This doctoral thesis will address the following research question:

How can smart meter data be processed and shared for the benefit of people and climate goals?

This overarching question is broken down into three sub-questions:

  1. What are the specific privacy and discrimination concerns for different user groups?
  2. What data features are needed by different stakeholder groups?
  3. What measures and processes are effective at safeguarding data privacy while maintaining valuable features?

The novelty of this thesis is in its unprecedented access to smart meter data and explanatory meta data, made possible by the EDOL project.

This opportunity will lead to three major advances over previous theoretical deliberations about privacy:

  1. This thesis will establish a scientific basis that can guide policy and regulation on the handling of energy relevant data, replacing arbitrary privacy rules with evidence led conditions for disclosure.
  2. The contextual socio-demographic information allows to establish the potential for discrimination and identification at a level that has hitherto not been possible with smart meter data alone.
  3. This thesis takes a citizen-centric approach and focuses on the benefits and costs for end- users, rather than merely the system or utilities


This studentship is funded through the UK Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Partnership and is open to Home students (full award – home fees plus stipend). Full details of the eligibility requirements can be found on the UK Research and Innovation website

Award Value

Course fees are covered at the level set for Home students plus UKRI minimum stipend.

Candidate Requirements

Prospective candidates will be judged according to how well they meet the following criteria:

  • A first class honours degree in Engineering, Physics or Materials Science
  • Excellent English written and spoken communication skills
  • Experience with data handling and privacy procedures
  • Ability to process socio-demographic information
  • Ability to conduct interviews and surveys

The following skills are desirable but not essential:

  • Ability to program in Python
  • Knowledge of and interest in energy demand
  • Social science experience
  • Energy policy experience

Application Procedure

Informal enquiries are encouraged and should be addressed to Dr Phil Grunewald (

Candidates must submit a graduate application form and are expected to meet the graduate admissions criteria.  Details are available on the course page of the University website.

Please quote 24ENGIN_PG in all correspondence and in your graduate application.

Application deadline: noon on 1 March 2024

Start date: October 2024