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AI & Health Entrepreneurship Associate (Public Health Track) Position Summary The AI & Health Entrepreneurship Associate (Public Health Track) is an applied, research-based internship/practicum opportunity designed for students and early-career professionals interested in advancing innovation at the intersection of public health, data, workforce development, and emerging technologies. This role supports the development and evaluation of community-centered, scalable public health solutions, integrating both quantitative and qualitative methods to better understand and address gaps in mental health, workforce pathways, and health equity. Organization Overview Voice Up is a research-driven public health and workforce innovation model with student engagement across 257+ higher education institutions and 42 countries. The organization operates through the Applied Purpose Science Research Lab to: identify and strengthen community-based contributors to health and wellbeing connect lived experience to health-related and purpose-driven pathways develop scalable models that integrate mental health, identity, and workforce systems Voice Up represents a non-traditional, community-embedded public health model focused on upstream determinants of health, prevention, and engagement. Location Remote (Global Participation Supported) Time Commitment Minimum 150 total hours (standard internship / MPH Applied Practice Experience) Flexible completion across one or multiple academic terms Eligibility Open to students and recent graduates from all academic disciplines, with strong alignment for: Public Health (MPH) Epidemiology Health Policy Health Administration Behavioral Health Data Science (health applications) Primary Responsibilities 1. Applied Public Health Research Conduct mixed-methods research, including: qualitative narrative analysis quantitative data tracking and interpretation Contribute to development of evidence related to: mental health engagement workforce pathways 2. Public Health Innovation & Systems Analysis Analyze gaps in: access to care workforce development community engagement Support development of innovative, scalable public health models 3. Health Pathways & Workforce Development Identify and map connections between: lived experience community engagement health-related career pathways Support development of pipeline and pathway frameworks 4. Ethical Use of Data and Technology Explore the role of AI and digital tools in public health contexts Apply principles of: ethics privacy responsible data use 5. Program Evaluation & Impact Measurement Track and analyze: participation engagement outcome indicators Contribute to evaluation reports and continuous improvement processes 6. Cross-Sector Collaboration Work across interdisciplinary teams Engage with participants across academic, community, and global contexts Learning Outcomes Participants will gain experience in: applied public health research (qualitative + quantitative) program evaluation and impact measurement workforce and pathway development systems ethical considerations in AI and public health systems thinking and policy-relevant analysis Preferred Skills and Competencies Strong analytical and critical thinking skills Interest in: data analysis public health systems innovation and entrepreneurship Effective written and verbal communication Ability to work independently in a remote environment Work Environment 100% Remote Flexible scheduling Research-driven, collaborative environment Application Instructions To apply, submit: Resume Cover Letter Email: Subject Line: AI & Health Entrepreneurship Associate (Public Health Track) Equal Opportunity Statement Voice Up welcomes applicants from all backgrounds and disciplines. We are committed to creating an inclusive environment that reflects the diversity of the communities we serve. In public health, this shift parallels the evolution from individual-level interventions to ecological models approaches that recognize behavior as embedded within systems of habit, environment, and social reinforcement. The work of on self-efficacy, and later research on habit formation and social norms, all converge on the same insight: people act consistently when behavior is structured, visible, and socially supported. The absence of that structure is what creates the gap. The Architecture of Disconnection The data embedded in the theory of change offers a subtle but revealing pattern. Participants report moderate overall wellbeing, but financial wellbeing and specifically financial openness emerges as the lowest domain .