RequestUpdated on 6 July 2025
Postdoc opprtunity in social or biomedical data science
associate professor at Budapest University of Technology and Economics
Budapest, Hungary
About
Research Team: The Human & Social Data Science Lab (HSDSLab) is a group of researchers at the Budapest University of Technology and Economics led by Dr Roland Molontay. HSDSLab conducts both methodology oriented basic research in data and network science and applied research with a human-centered and societal focus. The lab members develop statistical and computational methods to study the empirical, theoretical, and technical dimensions of all forms of data in social, policy, and business contexts. The Lab’s research includes predictive analytics in human health and education, user behavior analysis, data-driven assessment and evaluation in higher education, social network analysis, structural characterization of complex networks, explainable artificial intelligence in human-centered and social sciences, scientometrics.
For our researc projects and publications see: https://hsdslab.math.bme.hu/en/research.html
Research Interests: Our research group focuses on data-driven, human-centered approaches to understanding complex social, scientific, and health-related systems. We are currently engaged in projects in human-centered predictive analytics, educational data science, science of science, social media analytics, network embedding, and health data science. These projects involve the application of advanced machine learning, deep learning, and network science techniques to large-scale, real-world datasets. We welcome applications from researchers interested in these areas, particularly those with strong programming skills in Python, excellent verbal and written communication skills in English, and a keen interest in interdisciplinary research. Ideal candidates are curious about AI, machine learning, and network science, and are able to work independently as well as in collaborative settings. We offer a vibrant, supportive research environment with opportunities for impactful work at the intersection of data science and the social sciences or biomedical sciences.
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