AI and Geospatial Developer Archaeology and Cultural Heritage

Department

ISAC: CAMEL Lab Students and Temps

The Institute for the Study of Ancient Cultures was founded in 1919 by James Henry Breasted with the financial support of John

D. Rockefeller Jr., and was originally envisaged as a research laboratory for the investigation of the early human career that would trace humankind’s progress from the most ancient days of West Asia and North Africa. The goal of the Institute for the Study of Ancient Cultures is to be the world’s leading center for the study of the ancient civilizations of West Asia and North Africa by combining innovation in theory, methodology, and significant empirical discovery with the highest standards of rigorous scholarship.

The Institute for the Study of Ancient Cultures Museum was opened to the public in 1931. The majority of ISAC's collections are from its expeditions in West Asia and North Africa during the 1920s, 1930s, and 1940s. A major reinstallation of the Museum, including the construction of a climate-controlled wing for housing collections and archives, took place in the 1990s and early 2000s.

A complete renovation of the Museum was completed in 2019 in celebration of ISAC's centennial. The Institute for the Study of Ancient Cultures is a unit within the University of Chicago and the name of the corporation is 'The University of Chicago.' The corporation was originally incorporated on September 10, 1890.

The Institute for the Study of Ancient Cultures (ISAC) at the University of Chicago invites applications for a one-year funded position focused on developing Geospatial AI applications for archaeology, history, and cultural heritage. This is a unique opportunity to join an ambitious project at the University of Chicago that aims to transform how archaeology and historical researchers use archival satellite imagery and geospatial data for knowledge production on human-environment history.

The successful candidate will be responsible for the development of an open-source workflow and toolkit for AI-assisted remote sensing of historical satellite imagery. This will include a wide range of Dev Ops tasks, including designing geospatial data pipelines, integrating AI/ML models, writing and publishing code, writing docker images, and supporting collaborative, reproducible research environments in a Git environment. The position offers the chance to collaborate with a cross-disciplinary team of archaeologists, GIS specialists, and remote sensing experts, and to help establish the technological foundation for long-term international research.

This position is grant funded, and the length of the assignment is expected to be 12 months, with the possibility of continuation if additional funding is secured.

• Set up and configure geospatial AI/MLOps pipelines using existing libraries and frameworks, ensuring reproducibility and smooth deployment.
• Build and manage the infrastructure ecosystem (cloud and/or on-prem) to support geospatial remote sensing data processing.
• Implement and maintain remote sensing workflows, including data handling, processing, and basic results visualization and monitoring with standard open source tools.
• Effectively collaborate in a cross-disciplinary environment with archaeologists, geographers, historians, data scientists and computational engineers.
• Maintain excellent documentation to ensure reproducibility of workflows.
• Evaluate past and present technologies to help develop new tools. Ensure all the new tools have been through quality control reviews.
• Participate in the product development life cycle, providing professional assistance to the design of front-end applications and database systems back-end schema. Analyze high-level system specifications and make sure that all application development standards are met.
• Perform other related work as needed.

Education:

Minimum requirements include a college or university degree in related field.

Work Experience:

Minimum requirements include knowledge and skills developed through 2-5 years of work experience in a related job discipline.

• Experience in open-source development.
• Knowledge of cloud architectures and infrastructures (Open Stack, Kubernetes, etc.), and familiarity with HPC environments.
• Experience with geospatial libraries (GDAL/OGR, OTB, Geo Pandas, PySTAC, etc.) and machine learning frameworks (Scikit Learn, Keras/TF, PyTorch, etc.).
• Background in remote sensing, geospatial AI, familiarity with the following libraries: OTB/OTBTF or an equivalent geospatial processing framework, Keras/Tensorflow or an equivalent deep learning framework.
• Background or experience as a computer engineer, including the development and production of applications and software solutions.
• Experience in data science programming (mainly Python) and core libraries (Numpy, Pandas, etc.).
• Experience with the entire software development cycle, the implementation IDEs, code versioning (Git), and package/container…