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University of Cambridge

Postdoctoral Research Associate (evaluating food marketing restrictions) [Fixed Term]

Cambridge
Posted 1 day ago
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Postdoctoral Research Associate Evaluating Food Marketing Restrictions

Institute of Metabolic Science (IMS) Epidemiology

IMS Epidemiology is seeking to appoint a Postdoctoral Research Associate with skills and experience in quantitative methods for evaluation of natural experiments to contribute to a multi-component evaluation of new restrictions on marketing of less healthy foods.

Job Overview

New restrictions on advertising of less healthy food and drinks online and on TV before 9pm were implemented in the UK in January 2026. Restrictions on price-based promotions of less healthy products in England were implemented in October 2025.

Based in the Population Health Interventions Group, the primary role of this post is to lead quantitative analyses exploring the impact of the new restrictions on:

  1. Household grocery purchasing, using data purchased from Worldpanel by Numerator.
  2. Nutritional content of foods served by chain restaurants, using data from our MenuTracker database.

We anticipate that both pieces of work will use interrupted time series analysis methods.

Funding and Collaboration

Funded by the National Institute of Health Research (NIHR), we are conducting a multi-component evaluation of the restrictions. Across the whole evaluation, we will study impacts on marketing, availability and purchasing of less healthy products; model impacts on health and wider society; explore awareness and acceptability; and interrogate policy processes. The work is led from IMS Epidemiology and involves colleagues at the Universities of Oxford, Stirling, Exeter, Waterloo, and the London School of Hygiene and Tropical Medicine.

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Qualifications and Experience

  • Educated to PhD level in a relevant subject or due to complete within 3 months of applying.
  • Proven skills and experience in quantitative methods for evaluation of natural experiments, such as interrupted time series or difference-in-difference analysis.

A complete list of essential and desirable criteria for this post is provided in the further particulars. Your application is unlikely to be competitive if it does not provide clear and concise evidence that you meet all of the essential criteria.

Benefits and Conditions

  • Competitive salary.
  • Comprehensive package of benefits and services including discounts on shopping, private health care, financial services, and public transport.
  • Defined benefits pension schemes and tax-efficient bicycle, car lease, and charity-giving schemes.
  • This is a fixed-term position for 21 months.
  • The role can be performed as a hybrid position, recognizing that some tasks may only be performed on University premises.

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Application Process

  • Contact Professor Jean Adams, jma79@medschl.cam.ac.uk for informal enquiries.
  • Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.
  • Ensure you upload a covering letter and CV in the Upload section of the online application.
  • The covering letter should outline how you match the criteria for the post and why you are applying for this role.
  • Include details of your referees, including email address and phone number, one of which must be your most recent line manager.

Application Deadlines

  • Closing Date: 14th September 2026
  • Interview Date: 29th or 30th September 2026

Additional Information

  • Please quote reference SJ50788 on your application and in any correspondence about this vacancy.
  • The University actively supports equality, diversity, and inclusion and encourages applications from all sections of society.
  • The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
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Skills

Quantitative Methods
Natural Experiments Evaluation
Interrupted Time Series Analysis
Difference-in-Difference Analysis
Data Analysis
Epidemiology
Public Health Research

Location

Cambridge, England, United Kingdom

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