Postdoctoral Scholar - Nutrient Profiling, Food Quality, and Artificial Intelligence

What You'll Do

This is a full-time (12 months per year) position with an anticipated duration of 2-3 years, subject to annual review and renewal based on performance and available funding. The position is based in Boston, MA, and requires regular in-person work. Flexible and hybrid arrangements (e.g., 1–2 days per week remote) may be considered; fully remote work is not available.

The fellow will work within a close-knit, collegial multi-disciplinary team of other trainees, students, and staff within the Institute. In addition to mentoring from Dr. Dariush Mozaffarian, the fellow will interact with and gain knowledge and experience from a range of other expert faculty across the Institute and beyond.

• Updating and expanding the Food Compass algorithm according to the latest science, including expansion to include novel health-related bioactive attributes;
• Sustaining ongoing work and manuscripts, including related data manipulation and harmonization of large U.S. branded food databases, including application of AI tools for nutrient attribute coding, ingredient extraction, and large-scale dataset harmonization;
• Leading analyses describing dietary intake in the United States and internationally using Food Compass and existing dietary data from major data sources, including the National Health and Nutrition Examination Survey (NHANES), the USDA Branded Foods Database, UK Biobank, and others;
• Collaborating with food retailers, healthcare systems, international health-focused government agencies, nutrition-focused venture capital firms and coalitions, and other organizations to advance the role of NPS in consumer education and the creation a healthier and more equitable food environment;
• Disseminating research findings to relevant stakeholders, including the scientific community, food system leaders, legislative bodies, and advocacy groups and agencies.

Required Education, Experience and Skills

• An MD or doctoral degree (PhD, DrPH, ScD); additional training in biostatistics, coding, AI, epidemiology, nutrition, public health, economics, or related fields;
• A record of original, first-author research publications in relevant areas;
• Excellent quantitative/analytical research skills;
• Strong written and oral communication skills;
• Experience using analytic programs for data management and analysis (e.g., STATA, SPSS, SAS, R);
• Familiarity with AI tools for data processing, nutrient coding, and analysis of large food and dietary datasets;
• The ability to work well independently and as part of a team with collaborators.

Application Instructions

A complete application will include; cover letter, CV, and names of three references (if available, reference letters welcomed).

Applications should be submitted via Interfolio. Questions can be directed to Julia Sharib (julia.reedy@tufts.edu).