\\n \\n Doctoral position in Spatial-temporal information retrieval from multi-modal historical resources using GeoAI and LLM100%, Zurich, fixed-termIn recent years, geoinformation from historical maps has become a valuable resource for scientific studies as it allows for a continuous analysis of the evolution of man-made and natural features, such as cities, transportation networks, forests, and hydrological features. This is particularly important for urban planning, environmental management, and cultural heritage preservation.The digitization efforts of the Chair of Cartography in recent years have unlocked a vast amount of information from Swiss historical maps, facilitating comprehensive studies of spatio-temporal dynamics. When combined with historical resources from other modalities, such as textual archives, deeper spatio-temporal insights can be uncovered, providing researchers with a more comprehensive understanding of the past.This doctoral project aims to integrate diverse historical resources\\xe2\\x80\\x94primarily maps and texts\\xe2\\x80\\x94to enhance spatio-temporal information retrieval using GeoAI and Large Language Models (LLMs).Project backgroundThis doctoral research will focus on linking information in historical maps spatially and temporally with other resources, such as registries in historical documents. By integrating these diverse sources, the research will develop methodologies to extract, structure and organize historical data, enabling advanced search and retrieval. The outcomes will enhance the accessibility and usability of historical geospatial data, allowing for comprehensive cross-disciplinary analysis and deeper insights into historical events and transformations.Job description

• Extracting information from various sources (e.g., maps, texts, images) within a multi-modality framework.
• Registering historical maps from different times by leveraging advanced deep learning approaches.
• Building spatial-temporal knowledge graphs of historical resources with efficient database architecture.
• Integrating LLMs into knowledge graphs for information query.
• Publishing in peer-reviewed journals or present at equivalent conferences.
• Managing historical map data with Atlas of Switzerland and GeoVITE platform.
• Assisting teaching activities.

ProfileApplicants must have completed a Master\\xe2\\x80\\x99s degree in a related field (applicants completing their studies before June 2025 will also be considered)

• Master in Computer Science, Applied Mathematics, Remote Sensing, Geomatics or related.
• Experience with deep learning framework (e.g., Pytorch or Tensorflow).
• Experience with database management, preferably for geo-spatial databases (e.g., SPARQL, PostGIS).
• Knowledge of geospatial data formats, GIS tools and analysis methods.
• Experience with LLM framework (e.g., Langchain, LlamaIndex) is a strong plus.
• Excellent written and verbal communication skills.
• Ability to work independently and collaboratively in a team.
• Ability to manage research projects, including planning, resource allocation, and documentation.

WorkplaceWorkplaceWe offer

• Participate in a small, motivated research team.
• Pleasant working atmosphere.
• National and international network and collaboration.
• Benefits: usage of sport facilities and other university infrastructure on campus, contribution to the cost of public transportation (Halb-Tax and GA).

We value diversityIn line with , ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our to find out how we ensure a fair and open environment that allows everyone to grow and flourish.Curious? So are we.We look forward to receiving your online application with the following documents:

• One-page CV.
• One-page cover letter outlining research interests and experience.
• Copies of transcripts and diploma/certificates/degrees.
• Link to open-source data and code repositories (Zenodo and Github).
• Copies of relevant publications (if applicable).
• Reference letters and contact details of at least two referees.

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.Application Deadline: 3/31/2025; Starting date: 6/01/2025 (latest)Further information about the Institute of Cartography and Geoinformation can be found on our website https://karto.baug.ethz.ch. Questions regarding the position should be directed to Prof. Dr. Lorenz Hurni [lhurni@ethz.ch] or Dr. Yizi Chen [yizi.chen@ethz.ch] (no applications).For recruitment services the apply.About ETH Z\\xc3\\xbcrichETH Zurich is one of the world\\xe2\\x80\\x99s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.Curious? So are we.We look forward to receiving your online application with the following documents:

• One-page CV.
• One-page cover letter outlining research interests and experience.
• Copies of transcripts and diploma/certificates/degrees.
• Link to open-source data and code repositories (Zenodo and Github).
• Copies of relevant publications (if applicable).
• Reference letters and contact details of at least two referees.

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.Application Deadline: 3/31/2025; Starting date: 6/01/2025 (latest)Further information about the Institute of Cartography and Geoinformation can be found on our website https://karto.baug.ethz.ch. Questions regarding the position should be directed to Prof. Dr. Lorenz Hurni [lhurni@ethz.ch] or Dr. Yizi Chen [yizi.chen@ethz.ch] (no applications).For recruitment services the apply.\\n \\n \\n \\n \\n \\n

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