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Research Fellow

UCL - School of Life & Medical Sciences

Location: London, Hybrid
Salary: £43,374 to £51,860
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 6th March 2025
Closes: 26th March 2025
Job Ref: B02-08451

About the role

This role is part of a major NIHR-funded study evaluating the effects of real-world voluntary supermarket policies restricting the use of price promotions to sell unhealthy foods. The findings will provide important evidence for UK policymakers in advance of the wider adoption of the policy.

Price promotions or special offers, like two-for-the-price-of-one, are commonly used to sell less healthy food. Their use is particularly common in the UK, and evidence shows they encourage consumers to purchase more of these unhealthy products, which are linked to obesity and other diet-related diseases. Voluntary or mandatory restrictions on the use of price promotions have been proposed to limit their use, and support the marketing and sale of healthier products, in order to improve people’s health.

We are seeking a data scientist with strong quantitative skills to develop the protocol; and lead and undertake data analysis with the support of relevant Co-Investigators on two key projects that contribute to the evaluation:

  • Consumer Purchase Analysis: Purchase data for a single supermarket to assess how the changes in price promotions offered to loyalty card holders have changed, and how their food purchasing has changed as a result of the policy using natural experimental methods.
  • Health Impact Modelling: Adapting and developing, then applying an established public health model (PRIMEtime) to estimate how changes in food purchasing (from other analyses in the project) translate into population health outcomes (e.g., obesity and diet-related diseases) and healthcare costs.

This role involves preparation of large datasets (around 2 million records), conducting statistical analyses (including Interrupted Time Series Analysis), performing subgroup and sensitivity analyses, and preparing reports and publications for both academic and policymaking audiences.

The successful candidate will be part of a small team at GOS ICH (the ‘Public Health Approaches To Obesity Prevention’ team) and part of the wider NIHR research team collaborating with leading researchers from the partner institutions, including specialists in the field of Natural Experiments and one of the developers of the PRIMEtime model. This post is funded initially for 6 months and is then expected to be funded for 2 years in the first instance.

About you

We are looking for a motivated and analytical researcher with:

  • A PhD (or near completion) in epidemiology, public health, health sciences, or a related quantitative field. Candidates without a PhD will be appointed at Grade 6B, with progression to Grade 7 upon final submission of their PhD thesis without corrections.
  • Experience working with large quantitative datasets (cleaning, merging, and analysis). • Strong quantitative and regression analysis skills using statistical software (preferably R, Python or Stata).
  • Excellent written and verbal communication skills, with experience in presenting complex data to diverse audiences.
  • Ability to work both independently and collaboratively within a research team.

Customer advert reference: B02-08451

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