Digital Data Analyst position at University of Trento – deadline 12:00 of 23 February 2023

The Department of Sociology and Social Research of the University of Trento is hiring a research fellow to work in the context of the H2020 project CCINDLE – CO-CREATING INCLUSIVE INTERSECTIONAL DEMOCRATIC SPACES ACROSS EUROPE. The post is intended for performing research with intensive computational data analysis of large-scale datasets particularly of digtial data from the web and social media.

Duration of Contract: 12 months, approximately from 01.03.2023. The position is renewable for an additional 12 months.

Applications should be sent by 23 Feb. 2023, 12pm (Rome time).

The project

CCINDLE aims to enhance trust in democracy and to re-invigorate engagement with democratic institutions and values in Europe. It does so by co-creating solutions to the crisis of democracy, by designing and implementing strategies, which counter opposition to equality and democracy and by supporting citizens and activists working in this field. Its main attention foci are: i) antigender campaigns and how they challenge democracy, particularly through political violence and alternative knowledge production; ii) futures of society envisioned in feminist theories and how they relate to democracy in Europe with respect to intersectional justice, inclusion, and participation; iii) feminist movement and institutional responses to anti-gender and other anti-democratic forces.


  • Four or Five years degree/Master Degree in a data-oriented field: Data Science, Information Engineering and/or Computer Science; Artificial Intelligence; Physics, Mathematics and/or Statistics, Computational Social and/or Political Science; Social and/or Political Science awarded by an Italian or foreign university, or an equivalent qualification obtained abroad
  • Experience in collecting and managing large databases particularly (but not exclusively) from major social media platforms; experience analyzing using quantitative analysis methods and techniques; experience analyzing data using
  • techniques particularly (but not exclusively) from computational linguistics (NLP), network science (social and/or semantic), machine learning.
  • Excellent knowledge of the English language
  • Hold a professional-scientific CV in line with the research program described.
  • Two signed reference letters
  • Max. 5 publications showing the methodological skills of the candidate. Master and/or doctoral thesis is considered eligible among the submitted publications.

Submission Deadline: 23.02.2023,12:00 p.m.

Submission Procedure: Instructions (in Italian and English) are contained in the PDF available at this link

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