Postdoctoral Researcher in AI-Driven Data Curation and Data Integration

Responsibilities

• Develop AI-based methods and deploy them at scale to automate and augment data curation using Common Data Elements
• Design workflows to harmonize, validate, and enrich public datasets across Epilepsy, Immune Health, and NIH HEAL programs
• Develop novel mechanisms to interrogate, visualize, and interact with complex scientific datasets and increase the value of these datasets for the scientific community
• Integrate curation methods into scalable, cloud-based scientific data platforms
• Collaborate with the Pennsieve development team and scientific partners to align methods with real research workflows
• Evaluate and validate curation approaches using large, heterogeneous public datasets
• Prepare manuscripts, technical documentation, and presentations describing methods and outcomes

Qualifications

• Ph.D. (preferred) or Master’s degree in Biomedical Informatics, Computer Science, Data Science, Bioinformatics, or a related field
• Experience with machine learning, natural language processing, or AI applied to structured and unstructured data
• Familiarity with Common Data Elements, data standards, or ontology-based data representation (preferred)
• Strong programming skills in Docker, Python, Go, Java, or related languages
• Experience working with large-scale biomedical or clinical datasets
• Experience with cloud-based data processing and scalable analytics environments (AWS preferred)
• Strong written and verbal communication skills and an interest in interdisciplinary collaboration