# Skills and epistemic cultures in artificial intelligence research: evidence from job postings

## TL;DR

This study analyzes AI-related academic job postings to understand the skills and epistemic cultures emphasized in hiring.

## Contribution

It identifies seven distinct epistemic cultures and highlights evolving skill demands in AI research recruitment.

## Key findings

- There is a strong demand for research, digital, and communication skills in AI academic roles.
- Seven thematic clusters represent different epistemic cultures in AI job postings.
- The findings can guide policymakers and institutions in shaping AI research workforce strategies.

## Abstract

Artificial Intelligence (AI) has begun to transform the labor market, allowing technologies to perform some of the tasks previously performed only by humans. Previous studies have shown that artificial intelligence technologies have reshaped workplaces and tasks structures, generating new skill demands in the labor market. However, there is limited research on how the required skills and underlying epistemic orientations of AI-related academic jobs are communicated during the hiring process. The present study explores this discursive construction of the researcher role by analyzing the skills and competencies prioritized in AI-related academic job postings. To achieve the study's goals, we used data on job descriptions from around 800 jobs posted on the EURAXESS platform until January 2024 using descriptive text mining methods and Latent Dirichlet Allocation (LDA) topic modeling. The findings revealed a strong demand for research and digital skills, as well as career development, communication, mobility, and enterprise skills. The results also reveal seven distinct thematic clusters, which we interpret as representations of different epistemic cultures being signaled to prospective candidates. The results can be valuable for policymakers, research institutions, and universities.