About the C2DH The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The Luxembourg Centre for Contemporary and Digital History (CDH) at the University of Luxembourg is an interdisciplinary research centre committed to high quality research and public dissemination in the field of contemporary history with a particular focus on digital methods and tools. The CDH''s ambition is to venture off the beaten track and find new ways of doing, teaching and presenting contemporary history of Luxembourg and the history of Europe in the 20th and 21st centuries. It serves as a catalyst for innovative and creative scholarship and new forms of public dissemination. Your role As a Data Engineer in Digital History, you will support and advance data driven historical research by building and optimizing data pipelines in collaboration with CDH''s interdisciplinary teams and external partners to align data initiatives with historical research goals. You will work on implementing AI and GenAI technologies, including machine learning, natural language processing, and computer vision, to support complex historical data projects. This role is ideal for someone passionate about data engineering and committed to empowering historical research through robust, open, and standards based data infrastructures to ensure all data processes and pipelines are well documented and accessible. For further information, please contact Your profile The ideal candidate would have demonstrated experience in data engineering with the following profile: PhD in data science, computer science, engineering or related disciplines Required skills includes: Writing complex, highly optimized SQL and noSQL queries across large datasets Scripting languages like Python (e.g., Pandas, NLTK, Scikit learn, Keras, etc.), common LLM development frameworks (e.g., Langchain, Semantic Kernel) Experience with database technologies like SQL Server, MySQL, PostgreSQL, MongoDB, Neo4j, Elasticsearch Knowledge of GenAI, machine learning, deep learning, natural language processing, computer vision, and other AI technologies An excellent understanding of research data engineering tasks includes streamlining data integration and automation, managing scalable storage, ensuring data quality and reliability, and designing robust data models and architecture Familiarity with or interest in digital humanities and digital history datasets Experience that would be great or an interest in learning! includes: Building and managing data platforms using cloud infrastructures like Azure and/or AWS Skills in handling and processing multimodal data (text, audio, image) Experience or familiarity with exploring and implementing data protection and privacy in technical solutions to ensure responsible data use in line with global regulations, such as GDPR and the EU AI Act Passionate about using technology to conduct historical research and to suppo