We have an exciting and rare opportunity to join the prestigious Horizon Europe Doctoral Training Network, Data2Action, as a Doctoral Fellow. The successful candidate will be registered as a doctoral fellow at Glasgow Caledonian University and enrolled in the Data2Action Doctoral Network, with secondment opportunities in leading “Data for good” organisations.

Data2Action will train 13 Doctoral Fellows as the next generation of transdisciplinary social innovation leaders who are capable of ethically and responsibly developing state-of-the-art data science and artificial intelligence (AI) for social good. The network will bring together leading data science and AI researchers and experts with practitioners and experts in social innovation to conduct empirical research and cascading skill-building with the following objectives: 

Objective 1: Establish a research roadmap and framework grounded in empirical knowledge and best practices for data science/AI to power social innovation (Data/AI for Social Good). 

Objective 2: Demonstrate the potential and benefits across sectors of implementing social innovations powered by data science and AI through five demonstrator projects that showcase the impact on critical societal issues: Climate, Social justice, Democracy, and Health and Ageing.

Objective 3: Build capacity, Data/AI tools and methods for social innovators and entrepreneurs through an integrated open cascade training programme. 

Objective 4: Create new career pathways for data science and AI dedicated to social innovation. 

Objective 5: Provide guidance and support for practice about data science and AI for social innovation to stakeholders who contribute to social innovation: policymakers, funders, and governmental organisations and to data science and AI technology development. 

The Doctoral Candidate in the project Mining traditional and practitioner knowledge with data science to deliver Nature-based solutions for climate change adaptation will play a central role in the network.

The main objective of the research project of the doctoral candidate is to develop Artificial Intelligence (AI) tools to integrate traditional, practitioner and community knowledge to enhance the design and implementation of Nature-Based Solutions (NBS) to de-risk hydrometeorological risks. The key risks of focus of this project will be flooding and overheating. To achieve this, the fellow will:  

1) Curate GCU and partner data on NBS performance and be embedded in the Global South to both understand the context of NBS in which the data has been generated as well as site visits, interviews and fieldwork to undertake own top-up data collection.   

2) Carry out reverse innovation for applicability in the Global North.   

3) Develop AI tools employing advanced modelling and machine learning algorithms to answer questions around risk reduction, societal acceptance, anticipate potential challenges and barriers to the implementation of NBS in different contexts (urban and semi-urban). 

4) Work with ‘Nature-based Enterprises’ and other social innovators of the partnership to develop a long-term sustainability plan for NBS interventions to continue to provide the ecosystem services envisaged  

5) Facilitate public participation in NBS intervention plans to develop recommendations for suitable AI tools supporting social enterprises around NBS. 

The Doctoral Candidate will be expected to: 

• Report on findings by publishing scientific articles, resulting in a PhD dissertation;
• Present findings at (inter)national meetings/conferences;
• Contribute to the wider work of the Data2Action project
• Contribute to educational activities of the department and within the consortium.