Postdoc in Artificial Intelligence, Machine Learning, and Digital Humanities for Historical Manuscript Analysis

The University of Groningen invites applications for a postdoctoral position in Artificial Intelligence, focusing on machine learning, deep learning, and digital humanities within the HAICu research consortium. This role centers on developing advanced algorithms for the analysis of complex historical manuscripts, integrating continual learning and human-in-the-loop systems to address multimodal challenges such as layout analysis, logical reading order, and the detection of specialized textual and graphic patterns. As a postdoc, you will collaborate with PhD researchers, digital humanities experts, and cultural heritage institutions, including the Nationaal Archief, Collectie Overijssel, and Groninger Archieven. The position is based in the Department of Artificial Intelligence at the Bernoulli Institute, Faculty of Science and Engineering, University of Groningen, and is part of a multidisciplinary team working closely with the University of Twente and other partners. Key research areas include Artificial Intelligence, Machine Learning, Deep Learning, Digital Humanities, Historical Manuscript Analysis, Continual Learning, Human-in-the-loop Systems, Multimodal Analysis, and Pattern Recognition. The successful candidate will publish research in international journals and contribute open-access algorithms to project partners. Applicants must have a PhD in Artificial Intelligence, Machine Learning, Computer Science, or a related field, with a strong publication record, programming skills, and experience in machine learning and deep neural networks. Excellent English proficiency is required, and experience supervising students is advantageous. This is a fully funded, 3-year postdoctoral position offering a salary up to €4241 per month, 232 vacation hours per year, an end-of-year bonus, holiday allowance, and extensive professional development opportunities. The application deadline is March 14, 2026. For more information, contact Dr. Maruf Dhali at [email protected]. Apply online via the AcademicTransfer portal.