We have an exciting and rare opportunity to join the prestigious Horizon Europe Doctoral Training Network, Data2Action, as a PhD Fellow. The successful candidate will be registered as a fee free PhD student at Politecnico di Milano and enrolled in the Data2Action Doctoral Network, with secondment opportunities in industry and other European academic institutions.  

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. Find out more here: https://www.data2action.eu/. 

The Doctoral Candidate in the project Developing Data for Social Economy Investment Model and practice” will play a central role in the network and will: 

1. Review existing models and experiences in data exchanges, along with the EU regulatory landscape.  

This task involves conducting a literature review on the concept of data evaluation and an in-depth assessment of current practices in data-sharing environments. Additionally, it requires the acquisition of good knowledge of existing EU data-sharing regulations and a structured evaluation of their implications for data valuation.  

2. Develop multiple case studies on current data evaluation methodologies across different sectors.  

This task includes creating multiple case studies to examine the strengths and weaknesses of existing data evaluation models in various industries. The analysis will involve direct engagement with companies that sell data, as well as an assessment of their pricing models. Potential sectors of focus include telecommunications, insurance, banking and the energy sector.   

The task will conclude with a critical assessment of the applicability of these models within the social economy sector, culminating in a reference framework that highlights the challenges of valuing data in this domain.  

3. Develop a data evaluation methodology tailored to the social economy environment.  

This task aims to design a "data evaluation" model for data investment within the social economy. The process will begin with an analysis of investor-investee relationships in the impact finance market, with a particular focus on the role of impact quantification. By leveraging this knowledge, the candidate will explore how a data evaluation method can be effectively integrated into current practices and identify the processes and tools needed to quantify data value. The final output may involve adapting existing methodologies to better suit the unique characteristics and needs of social enterprises.  

4. Co-create and test a pilot model for social innovation in real-world settings.  

This task involves co-developing a "data investment" process using the methodologies established in the previous phase. The goal is to facilitate the transfer of data from data holders to social enterprises. The co-development and subsequent testing will be carried out in collaboration with key partners such as Fondazione Triulza, Rethink Ireland, and SIX (Social Innovation Exchange UK). The model will be tested on three to four real-life projects.  

5. Disseminate findings and contribute to academic discourse.  

The candidate will document each stage of research, design, development, and evaluation. They will actively participate in academic conferences and publish research articles to share insights with the broader research community.