Doctoral Researcher (PhD student) in the field of medieval and/or early modern history / historical cartography

The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The University was founded in 2003 and counts more than 6,700 students and more than 2,000 employees from around the world. The University’s faculties and interdisciplinary centres focus on research in the areas of Computer Science and ICT Security, Materials Science, European and International Law, Finance and Financial Innovation, Education, Contemporary and Digital History. In addition, the University focuses on cross-disciplinary research in the areas of Data Modelling and Simulation as well as Health and System Biomedicine. Times Higher Education ranks the University of Luxembourg #3 worldwide for its “international outlook,” #20 in the Young University Ranking 2021 and among the top 250 universities worldwide. 

The Institute for History (IHIST) brings together researchers from the fields of history, archaeology, cultural anthropology and sociology. Research at IHIST ranges from Antiquity to today, and by eschewing periodization, the continuities and changes over the long term are emphasized. The historical areas forming today’s Luxembourg and Greater Region, the crossroads of Europe, constitute a stimulating case study for historical investigation of Borders and Identity, Power and Legitimation, History and Space, Materiality and Culture.

The successful candidate will become a member of the Doctoral Training Unit “Deep Data Science of Digital History” (D4H). This interdisciplinary DTU focuses on multiple challenges at the intersection between the disciplines of history and data science. The DTU will train a new generation of digitally literate PhD students to deal with “big data of the past” in a critical and competent way, combining the epistemic tradition of close reading with machine-based methods of distant reading (“scalable reading”). It aims to develop a shared understanding of the human/machine nexus in collecting, curating, managing, analysing, interpreting, and visualizing historical data and to problematize the multi-layered temporalities of datasets and experiment with new forms and formats of historical models and simulations in a longue-durée / deep time perspective.