University of Chicago
AI and Geospatial Developer for Archaeology and Cultural Heritage
University of Chicago, Chicago, Illinois, United States, 60290
AI and Geospatial Developer for Archaeology and Cultural Heritage
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AI and Geospatial Developer for Archaeology and Cultural Heritage
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University of Chicago Job Summary
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 that aims to transform how archaeology and historical researchers use archival satellite imagery and geospatial data for knowledge production on human‑environment history. Responsibilities
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 and ensure all new tools have undergone quality control reviews. Participate in the product development life cycle, providing professional assistance to the design of front‑end applications and back‑end database systems, and analyze high‑level system specifications to meet application development standards. Perform other related work as needed. Qualifications
Minimum Qualifications College or university degree in a related field. Work Experience 2–5 years of relevant experience in a related discipline. Preferred Qualifications
Experience in open‑source development. Knowledge of cloud architectures and infrastructures (OpenStack, Kubernetes, etc.) and familiarity with HPC environments. Experience with geospatial libraries (GDAL/OGR, OTB, GeoPandas, PySTAC, etc.) and machine learning frameworks (Scikit‑Learn, Keras/TensorFlow, PyTorch, etc.). Background in remote sensing, geospatial AI, familiarity with libraries such as 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 management (Docker, Singularity, etc.). Working Conditions
Work occurs in a hybrid environment with time split across offices, labs, and digital platforms. Occasional lifting of materials (up to 30 lbs) and participation in outreach or instructional events may be required. Application Documents
Resume (required) Cover Letter (required) Professional References (three required) When applying, upload all documents via the
My Experience
page, in the section titled
Application Documents . Pay and Benefits
Salary: $70,000.00 – $85,000.00 Exempt, 37.5 weekly hours, FLSA Status: Exempt Benefits: Health, retirement, and paid time off. Eligible employees receive a comprehensive benefits package. Equal Opportunity Employment
The University of Chicago is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, or expression, national or ethnic origin, shared ancestry, age, status as an individual with a disability, military or veteran status, genetic information, or other protected classes under the law. For additional information please see the University’s Notice of Nondiscrimination. All offers of employment are contingent upon a background check that includes a review of conviction history.
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Join to apply for the
AI and Geospatial Developer for Archaeology and Cultural Heritage
role at
University of Chicago Job Summary
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 that aims to transform how archaeology and historical researchers use archival satellite imagery and geospatial data for knowledge production on human‑environment history. Responsibilities
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 and ensure all new tools have undergone quality control reviews. Participate in the product development life cycle, providing professional assistance to the design of front‑end applications and back‑end database systems, and analyze high‑level system specifications to meet application development standards. Perform other related work as needed. Qualifications
Minimum Qualifications College or university degree in a related field. Work Experience 2–5 years of relevant experience in a related discipline. Preferred Qualifications
Experience in open‑source development. Knowledge of cloud architectures and infrastructures (OpenStack, Kubernetes, etc.) and familiarity with HPC environments. Experience with geospatial libraries (GDAL/OGR, OTB, GeoPandas, PySTAC, etc.) and machine learning frameworks (Scikit‑Learn, Keras/TensorFlow, PyTorch, etc.). Background in remote sensing, geospatial AI, familiarity with libraries such as 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 management (Docker, Singularity, etc.). Working Conditions
Work occurs in a hybrid environment with time split across offices, labs, and digital platforms. Occasional lifting of materials (up to 30 lbs) and participation in outreach or instructional events may be required. Application Documents
Resume (required) Cover Letter (required) Professional References (three required) When applying, upload all documents via the
My Experience
page, in the section titled
Application Documents . Pay and Benefits
Salary: $70,000.00 – $85,000.00 Exempt, 37.5 weekly hours, FLSA Status: Exempt Benefits: Health, retirement, and paid time off. Eligible employees receive a comprehensive benefits package. Equal Opportunity Employment
The University of Chicago is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, or expression, national or ethnic origin, shared ancestry, age, status as an individual with a disability, military or veteran status, genetic information, or other protected classes under the law. For additional information please see the University’s Notice of Nondiscrimination. All offers of employment are contingent upon a background check that includes a review of conviction history.
#J-18808-Ljbffr