This study aimed to design an optimal model for the governance of science and technology within the higher education system. Adopting a qualitative approach, this research utilized Grounded Theory. The participants included 14 experts in higher education management and policymakers from the Ministry of Science, Research and Technology, selected through purposive sampling as key informants. Data were collected via semi-structured interviews. To ensure validity and reliability, participant member checking and re-coding by experts were employed. Data analysis involved open, axial, and selective coding, resulting in the identification of 167 open codes and 25 categories.

The findings indicate that the optimal model for science and technology governance in higher education can be explained through six key dimensions:

Causal Conditions: Including governance and policymaking, university autonomy, scientific diplomacy and global networking, and institutional restructuring and agility. Core Conditions: Comprising optimal and integrated governance of science and technology, mission-oriented and strategic problem-solving, knowledge co-creation and ecosystem interactions, and data-driven governance and technological transformation. Contextual Conditions: Focusing on empowering intellectual capital, scientific meritocracy, a learning and innovation-oriented culture, financial sustainability, and governance stability.

Intervening Conditions: Addressing domains such as university autonomy, structure and management, societal interactions, human resources, finance, digital transformation, international relations, and socio-cultural aspects. Strategies: Focusing on institutional integration and alignment, multi-level governance coordination, academic decentralization, and smart regulation for emerging technologies.

Consequences: Including increased efficiency and productivity of the higher education system, sustainable growth, and national competitiveness.

Finally, the paradigmatic model of the research was presented.