Assistant Professor
Biography
Sam Muller is an assistant professor at the University Medical Center Utrecht's Julius Center for Health Sciences and Primary Care's subdepartment of Bioethics and Health Humanities. With a background in political science and public administration and organisational science, Sam has previously researched innovations and challenges relating to the topics of (network) governance, citizen participation, and deliberative democracy. In addition, he has undertaken research into political theory and climate policy and governance.
Sam's research focuses on responsible governance of health research networks. His research is highly interdisciplinary, intersecting the social sciences (public administration and organisational science, political science, sociology, policy studies), applied ethics (research ethics and bioethics), and science, technology and society (STS). This approach enables studying the heterogeneous normative - social and ethical - dimension in which complex network governance processes take place. Sam is currently working on diffused responsibilities in collaborative health research, development of deliberative processes within responsible governance, responsible surveillance, and stakeholder ecosystem mapping and network analysis.
Sam's PhD research concerned responsible governance of Big Data-driven health research, titled "Responsible governance for data-intensive health research networks: A learning approach". His PhD research was part of the work package addressing the governance, ethical and legal aspects of the Innovative Medicines Initiative's (IMI) BigData@Heart project. By addressing the three challenges of accommodating ethical and legal fragmentation, connecting with stakeholders and society, and managing intractability, heterogeneity and complexity, its aim was to develop an approach enabling responsible governance suitable for Big Data-driven health research taking place in networks. Learning governance provides a pragmatic and intuitive way to realise governance for data-intensive health research networks, with due regard for the complex social, institutional and structural context in which governance is situated. Learning governance highlights the self-regulating role of governance for data-intensive health research networks. Moreover, governance is socially sanctioned and depends on a mandate provided by its stakeholders/ Governance fulfills a self-organising function for which incremental learning is essential. Therefore, experimentalist design, strengthening collective control and participatory governance are crucial.
