Post-Doctoral Researcher at UNU-MERIT

Project background:

The PILLARS project (2021-2023), funded by the European H2020 research programme, studies how changes in emerging automation technologies, their adoption along GVCs, and related industrial transformations, affect the future of work through the reconfiguration of the demand for skills. The main objective of PILLARS is to provide policy makers and the public with information about what kind of skills will be in demand and how to revise education and training systems to create the opportunities to acquire them.
The PILLARS project consists of ten partners, eight EU partners and one partner in China and in Latin America. You can find further details on the project here , or by contacting the project members (below).

Job description:

The main goal of this position is to support the design, analysis and administration of a large real-time Delphi survey to gauge the development and adoption potential of automation technologies in the near future (i.e. a decade) across industries. It will complement results from the analysis of unstructured (big) data on science and technology and innovation that is running in parallel.

The Research Fellow will primarily focus on conducting a large-scale global online Delphi survey to gather intelligence on which automation technologies are likely to advance in the near future, in which industries they will be adopted, and to conduct which tasks.

The Research Fellow will:

• use Delphi techniques to design the survey, together with a team at UNU-MERIT and Technopolis Group, and in collaboration with all other project partners;
• use standard statistical analysis methods to parse and analyse the data, as well as text and sentiment analysis to analyse the discussion within the responses;
• support the organisation of workshops in five different countries to conduct focus groups with a selected group of experts, to discuss results from the Delphi survey and data analysis;
• work alongside the project team in UNU-MERIT, SPRU (University of Sussex) (and in collaboration with other partners) that are using data mining, machine learning, and text analysis methods to analyse unstructured data on Science, Technology and Innovation (STI) to identify emerge technologies, and estimate the industry exposure to these.

The Research Fellow will work in collaboration with a team of top innovation scholars, economists, and job market data scientists in UNU-MERIT, SPRU and partner organisations, and two Research Fellows on data science. The Research Fellow will participate in several projects meetings and workshops to refine survey design, as well as external conferences and workshops.