In the context of the upcoming interdisciplinary project "impresso - Media Monitoring of the Past II" ("impresso doppio"), the EPFL Digital Humanities Laboratory is looking for a post-doctoral researcher who will work with us on the design, development and evaluation of large-scale text mining pipelines for multilingual historical newspaper and radio archives. About EPFL: EPFL, the Swiss Federal Institute of Technology in Lausanne, is one of the most dynamic university campuses in Europe and ranks among the top 20 universities worldwide. The EPFL employs more than 6,000 people supporting the three main missions of the institutions: education, research and innovation. The EPFL campus offers an exceptional working environment at the heart of a community of more than 16,000 people, including over 12,000 students and 4,000 researchers from more than 120 different countries. About the project: "impresso - Media Monitoring of the Past II" is an interdisciplinary research project which aims to pioneer new approaches to the joint exploration of newspaper and radio archive contents across time, languages, and national borders. Funded by the Swiss National Science Foundation and the Luxembourg National Research Fund (2023-2027), it is carried by the EPFL DHLAB, the Department of Computational Linguistics of the University of Zurich, the Centre for Contemporary and Digital History (C2DH) and the History Department of the University of Lausanne, with the additional support of 21 European partners. Computational linguists, computer scientists, digital humanists, historians, and designers will work closely together to enrich and connect newspaper and radio sources through multiple layers of cutting-edge semantic enrichments represented in a shared multilingual vector space, and to design adequate, meaningful and transparent exploration capabilities for (data-driven) historical research in transnational and transmedia perspective. Impresso doppio follows on from the first impresso project which developed a scalable architecture for the processing of Swiss and Luxembourgish newspaper collections and created an interface with powerful search, filter and discovery functionalities based on semantic enrichments. The present project puts forward the vision of a complete connection between media archives across languages and media types. Application deadline: 21.04.2023 Interviews: End of April. Place of work: EPFL DHLAB, Lausanne, Switzerland. Salary: according to EPFL salary scales and experience. How to apply: please upload your application (full CV and cover letter) via this portal. Post-doctoral Researcher in Natural Language Processing Your mission : You will conduct research in natural language processing and text mining on historical texts, with the aim of developing powerful information extraction methods on heterogeneous, multilingual and challenging radio transcripts and newspaper archives. Main duties and responsibilities include : Key responsibilities - Develop approaches to advanced named entity processing, quote extraction and segmentation and classification of media content. - Contribute to semantic indexing integration of media archives. - Contribute to the co-design of the interface and dedicated developments supporting the 4 historical use cases of the project. - Contribute to the organisation of international evaluation shared tasks on historical document processing. - Contribute to the organisation of project workshops on media mining, semantic indexing and processing pipelines. - Participate in other impresso work packages where your expertise is required and coordinate with project team members and partners. - Presentation of research results and participation in scientific and communication events. - Assistance with project management and organisational tasks. Your profile : - PhD (obtained or close to completion) in natural language processing, machine learning, computer science or related areas. - Strong background in machine learning foundations and willingness to apply approaches to real and large-scale data. - Experience in deep learning, language models, information extraction. - Strong programming skills (Python, deep learning frameworks) and knowledge of Unix-based operating systems. - Curious, creative and highly motivated about scientific research and the application of NLP to digitised cultural heritage collections. - Very good communication, presentation, and writing skills in English. - Comfortable in an international and multi-cultural context. Desirable: - Experience of working with historical documents and in an interdisciplinary environment. - Understanding of image processing is a plus. - Knowledge of French or German is a plus. - Willingness to (co)-supervise student projects, internships and master theses. We offer : - Opportunity to join an experienced and highly motivated interdisciplinary team conducting innovative and relevant research at the intersection of computer science and humanities research. - Applied research framework: what you will develop will be deployed in production and directly used by a community of researchers. - Work in an interdisciplinary team at the intersection of computer science, NLP, history, journalism and digital library. - Flexible working hours and teleworking. - Located in Lausanne, Switzerland, EPFL has a highly international environment, state-of-the-art research facilities, and is consistently ranked among the world's leading institutions in scientific research. Lausanne is a vibrant and cosmopolitan city centre in a unique natural environment with great outdoor activities (Jura, Alps, Lake Leman). Salaries and benefits are internationally competitive. Start date : Foreseen start of contract: 01.09.2023 Term of employment : Fixed-term (CDD) Duration : 3.5 years (1-year contract renewable until the end of Feb 2027) Contact : For any questions, feel free to contact Maud Ehrmann maud.ehrmann@epfl.ch Remark : Only candidates who applied through EPFL website or our partner Jobup's website will be considered. Files sent by agencies without a mandate will not be taken into account. Reference : Job Nb 2822 apply online https://recruiting.epfl.ch/Vacancies/2822/Description/2