Postdoc: AI-Driven Data Curation & Integration

University of Pennsylvania Perelman School of Medicine; Erie (Erie County); On-site; USD 55,000 - 70,000; Full time

Job summary

The Wagenaar Lab at the University of Pennsylvania Perelman School of Medicine invites applications for a Postdoctoral Researcher to advance AI-enabled data curation using Common Data Elements and large biomedical datasets.

The role spans collaboration with the Pennsieve development team to design reproducible, scalable curation workflows and to contribute to peer-reviewed publications and open-source resources in data stewardship and reuse.

Qualifications

• Ph.D. preferred or Master’s degree in Biomedical Informatics, Computer Science, Data Science, or related field.
• Experience with machine learning, NLP, or AI applied to structured/unstructured data.
• Familiarity with Common Data Elements or ontology-based data representation is a plus.
• Strong programming skills in Docker, Python, Go, Java, or related languages.
• Experience with large-scale biomedical/clinical datasets and cloud processing (AWS preferred).

Responsibilities

• Develop AI-based methods and deploy at scale to automate data curation using CDEs.
• Design workflows to harmonize and enrich public datasets across disease programs.
• Create visualization and interaction tools for complex biomedical datasets.
• Integrate curation methods into scalable cloud-based platforms.
• Collaborate with Pennsieve and partners to align with real research workflows.
• Prepare manuscripts, technical docs, and presentations describing methods and outcomes.

Skills

Python

Docker

Go

Java

Machine Learning

NLP

Cloud AWS

Interdisciplinary collaboration

Education

PhD or Master’s in a related field

Tools

Pennsieve

Job description

The Wagenaar Lab at the University of Pennsylvania Perelman School of Medicine invites applications for a Postdoctoral Researcher to advance AI-enabled data curation using Common Data Elements and large biomedical datasets.

The role spans collaboration with the Pennsieve development team to design reproducible, scalable curation workflows and to contribute to peer-reviewed publications and open-source resources in data stewardship and reuse.