**Job Description**
The Data Science for Dynamic Intervention Decision-Making Center seeks a UX Research Specialist to assist Drs. Benson and Newman with a research project focused on “Personalized Feedback Visualizations for Just-In-Time Adaptive Interventions” for smoking cessation. The project involves conducting co-design sessions to help design mobile app-based personalized feedback visualizations and a quantitative proof of concept study to develop and examine visualization prototypes. The specialist will contribute to the design and refinement of visualizations reflecting dynamic health behavior experiences.
**Skills & Abilities**
• Strong UX and data visualization skills
• Experience with conducting and analyzing qualitative interview data (highly valued)
• Experience with user-centered design methods, including co-design and iterative prototyping
• UX study design
• Participant recruitment
• Leading co-design sessions and conducting semi-structured interviews
• Analysis of semi-structured co-design and interview data
• Experience designing digital interfaces, ideally with a portfolio demonstrating health-or behavior-related visualizations or other personal informatics tools
• Excellent visual communication and information design skills
• Proficiency with design tools (e.g., Figma)
• Ability to work well in both team-based and independent settings
• Strong interpersonal skills and ability to translate research insights into intuitive user experiences
• Experience designing or evaluating mobile health (mHealth) or digital behavior change interventions (desired)
• Familiarity with just-in-time adaptive interventions (JITAIs) or intensive longitudinal data (e.g., ecological momentary assessments) (desired)
• Knowledge of persuasive technology frameworks (desired)
**Qualifications**
Required Degree(s) in:
• UX Design
• Human-Computer Interaction
• Information Design
• Psychology
• Public Health
• Related field
**Experience**
Other:
• Experience designing behavior change tools, personal informatics, and/or personal data visualizations (especially in health, psychology, or mobile contexts)
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