MSCA Fellowship

Responsibilities

• Develop a theory of transformative change for embedding Data Science and AI in Social Innovation practice. This will involve:
  • Designing and conducting a systematic review of academic and grey literature to identify existing knowledge gaps.
  • Designing and conducting survey/interviews to/with social innovation ecosystem actors across the EU to capture diverse perspectives and challenges.
  • Desktop-mapping best practices to highlight successful or unsuccessful AI and data science integration cases.
  • Triangulating findings from the above data collection methods using a realist synthesis methodology (Wang et al., 2013) to develop a robust theoretical framework (middle-range theories) hypothesising what works, for whom, and how to embed data science and AI in social innovation practice.
• Test the theory developed for embedding data science and AI in Social Innovation practice. This will involve:
  • Designing and implementing a multiple case study strategy able to test the middle-range theories developed.
  • Conducting primary data collection aligned with the case-study approach, including a combination of qualitative methods (interviews, focus groups, and document analysis) to explore the contextual factors that influence the integration of data science and AI in social innovation practice.
  • Analysing and synthesizing evidence into a refined middle-range theory that explains AI and data science integration in social innovation.
• Develop a co-creation process to define a framework and guidance to practice for embedding data science and AI in social innovation. This will involve:
  • Identifying key stakeholders and engaging with them in a formal evidence-based co-creation process following standardised methodology (i.e. PRODUCES www.healthCascade.eu).
  • Developing a co-creation protocol guided by the “Matching Data to Problems to Partners” model to design the framework that enables different participants to interact and co-create value.
  • Designing and facilitating workshops, design sprints, and iterative feedback loops to refine the framework with key practitioners, policymakers, and data science and AI specialists.
  • Developing a guidance document and toolkit to enable policymakers, social entrepreneurs, and organizations to implement AI-driven social innovation more effectively.

Skillset

• Eligible applicants must possess or be finalising a Master’s degree or an equivalent degree in a relevant discipline for Data2Action. Possible disciplines include e.g., management, economics, public policy, sociology, computer science, artificial intelligence, ICT engineering, digital humanities, law, philosophy, philosophical ethics, health sciences. Click here for more information on Master’s degree or an equivalent degree eligibility requirements.
• Excellent English language proficiency. Click here for more information.
• Competencies: Open-minded, self-aware, collaborative, critical thinker, team player, strong communicator.
• Applicants must be available full-time to start the program in September 2025.