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Study and Career

ESRC-ADR UK No.10 data science fellowships 2021

  • Funders: Economic and Social Research Council (ESRC)    
  • Co-funders: Administrative Data Research UK (ADR UK)
  • Funding type: Fellowship
  • Maximum award: £135,000
  • Closing date: 2 June 2021 16:00 UK time    

Apply for funding to spend a year collaborating with 10 Downing Street’s data science team (10DS) and the Office for National Statistics (ONS).

You will:

  • co-design research and produce analysis using new and existing linked administrative datasets to inform policy in priority policy areas
  • champion data science across central government and support wider knowledge exchange with researchers on effective policy collaboration and data analysis.

The datasets will be accessed through the ONS’ Secure Research Service.

You must:

  • have a PhD or equivalent experience
  • be a social science-focused researcher based at an eligible UKRI research organisation
  • have relevant quantitative analytical experience.

They will fund 80% of the full economic cost of the fellowship. Funding will last up to 18 months to cover:

  • inception phase for project set up, three months
  • placement with 10DS, 12 months
  • impact phase, up to three months.

This fellowship is available on either a full-time or part-time basis.


Who can apply

This opportunity is open to economic and social science researchers or those working at the intersection between economic and social science disciplines and fields such as computer science, statistics, and applied mathematical modelling. Applicants must hold a PhD or equivalent experience and be based at an eligible UKRI research organisation.

The opportunity is particularly targeted at early to mid-career academics. It is a requirement that early career applicants are provided with appropriate mentorship by a more senior academic with relevant experience from within their institutions, and this will be funded through the award. In addition, project-specific mentorship may also be funded if this is identified as necessary during the inception phase.


Person specification

You must:

  • be an economic or social science researcher or a researcher working at the intersection between economic and social science disciplines and fields such as computer science, statistics, and applied mathematical modelling
  • be based at an eligible UKRI research organisation
  • hold a PhD or equivalent
  • have expertise in and experience of applying data science techniques and methods, including working with novel data sets and assessing data quality and reliability
  • have experience of working effectively at pace, including as part of a team on shared goals
  • have excellent written and verbal communication skills, and the ability to translate complex information into meaningful, easily understood narrative that is accessible to a non-academic audience

In addition, they welcome applications from individuals who can demonstrate:

  • subject matter expertise relevant to one or more of the potential cross-cutting government priorities, or expertise that can be transferred and applied to topics such as these
  • experience of stakeholder engagement and collaboration
  • experience of working in a governmental context
  • experience of designing and leading on knowledge exchange activity between research, policy and funder communities


How to Apply

Applications will be made through the Joint Electronic Submission system (Je-S). To be able to do this your host organisation must be registered for Je-S, and you must hold a Je-S account. If you are unsure about this you should contact your research organisation’s research office for further guidance.

Please see the Je-S guidance attachment (PDF, 314 KB) for in-depth information about the application process.

When applying select:

  • council: ESRC
  • document type: Fellowship
  • scheme: Research Fellowship
  • call/type/mode: ESRC ADR UK No 10 Data Science Fellowships 2021

Mandatory attachments:

  • case for support
  • CV, including one-page publication summary list
  • justification of resources
  • Head of Department statement
  • mentor CV (if applicable).
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