Bibliometric Analysis Specialist (Python & Data Visualization)

We are seeking a data-driven researcher to conduct a bibliometric analysis on the scholarly landscape of Digital Humanism. The successful candidate will extract, clean, and analyze publication data using Python (with Pandas), and produce insightful visualizations to map trends, networks, and key themes in this emerging field.

Gather bibliographic data from major academic databases (e.g., Scopus, Web of Science, IEEE Xplore) related to Digital Humanism.
Clean, preprocess, and organize publication metadata using Python and Pandas.
Perform bibliometric analyses: publication trends, citation analysis, co-authorship networks, keyword co-occurrence, and thematic mapping.
Create clear and engaging visualizations (using Matplotlib, Seaborn, Plotly, etc.) to communicate findings.
Summarize and interpret results in reports for both technical and non-technical audiences.
Collaborate with subject matter experts to ensure relevance and accuracy of insights.