Postdoctoral Associate

Job Summary: The NYU Program of Nutrition at Steinhardt and the Institute of Human Development and Social Change (IHDSC) are seeking a Postdoctoral Associate to support Dr. Angela Trude and the OPT-FRESH research team. This role will provide comprehensive involvement in all aspects of the project, including protocol development, data collection and analysis, manuscript preparation, and dissemination of study findings. The Postdoctoral Associate will devote 12 person-months of effort each year to the project, Data Management and Sharing activities, assisting the Data Manager with data curation and documentation. 

Project Overview: OPT-FRESH is a 5-year NIH-funded intervention trial addressing gaps in healthy food access among low-income families. Using the multiphase optimization strategy (MOST), the study tests three intervention components designed to reduce barriers to online healthy food purchases: 1) weekly text messages to improve trust in online grocery services; 2) weekly match of up to $10 as a financial incentive for purchasing FVL online; and 3) weekly instant shoppable grocery lists of tailored meal suggestions using SNAP-Ed recipes. OPT-FRESH will provide a unique opportunity to identify effective, scalable, and efficient strategies that could be used to reach the over 44 million people in the U.S.,  including six million children, experiencing food insecurity, thus addressing important social determinants of health that explain health disparities related to cardiovascular disease. 

Specific Responsibilities: 

1. Support the PI and research team in all aspects of study design, protocol development, and implementation. 
2. Conduct data collection, management, and analysis, including qualitative and quantitative methods. 
3. Assist the Data Manager with Data Management and Sharing activities (e.g., data curation, documentation, compliance with NIH data-sharing requirements). 
4. Contribute to manuscript writing, grant proposals, and dissemination of findings through academic presentations, policy briefs, and community reports. 
5. Facilitate communication and collaboration among investigators, research staff, and community partners. 
6. Support supervision and mentoring of graduate research assistants and student volunteers.
7. Participate in regular team meetings, workshops, and events related to the project. 

Working Conditions

In-person: meetings, recruitment, and data collection will be in-person. Meetings will be conducted in the NYU Washington Square Campus, where the Postdoctoral Associate will have a designated work-desk and computer. Recruitment and data collection will occur in the Bronx. Public transportation costs related to recruitment and data collection are reimbursed. 

Time Frame

One-year position with potential renewal for up to five years. 

In compliance with NYC's Pay Transparency Act, the annual base salary range for this position is $62,500-$65,000. New York University considers factors such as (but not limited to) the specific grant funding and the terms of the research grant when extending an offer. 

Per NYU's remote-work policy, this position is expected to be completely in-person. 

This position will have some supervisory responsibilities, assisting the Project Coordinator in supervising at least 4 graduate student researchers and student volunteers. 

Qualifications and Competencies:

1. PhD in Nutrition, Public Health, Food Policy, or a related field.
2. Strong background in research methods, including study design, data collection, and analysis. 
3. Experience with Data Management and Sharing practices, including data curation and documentation. 
4. Demonstrated record of scientific writing and dissemination. 
5. Experience with community-engaged research, interventions, or public health programs preferred. 
6. Strong organizational, interpersonal, and collaborative skills. 
7. Sensitivity to racial, cultural, and economic diversity; familiarity with NYC communities preferred. 
8. Willingness to travel locally within New York City for recruitment and data collection.