Postdoc: Cloud-Driven Biomedical Data Scientist (Geospatial)

University of North Carolina at Chapel Hill; Chapel Hill (NC); On-site; USD 65,000 - 75,000; Full time

Benefits offered by this job

Comprehensive medical and vision coverage

Paid leave and benefits supporting professional development

Healthy work/life balance support

Job summary

The University of North Carolina at Chapel Hill is looking for a Post-Doc Research Associate in the Department of Genetics. This role focuses on innovative methods linking environmental data and clinical research in a secure cloud to support biomedical research.

The position offers a salary range of $65,000 - $75,000, comprehensive medical benefits, and support for professional development. Applicants should hold a PhD and have experience with geospatial environmental data analysis, collaborative programming in Python, and working within distributed teams.

Qualifications

• PhD required; experience in analysis, management, or integration of geospatial environmental data.
• Experience with collaborative programming in GitHub using Python.
• Ability to work with a geographically distributed team.

Responsibilities

• Design and implement robust pipelines for ingesting and QA/QC of datasets.
• Refine and maintain clinical research data models for cloud analytics.
• Develop and support geospatial data visualizations.

Skills

Geospatial environmental data analysis

Collaborative programming in GitHub using Python

Data management and integration

Education

PhD in any STEM field

Job description

The University of North Carolina at Chapel Hill is looking for a Post-Doc Research Associate in the Department of Genetics. This role focuses on innovative methods linking environmental data and clinical research in a secure cloud to support biomedical research.

The position offers a salary range of $65,000 - $75,000, comprehensive medical benefits, and support for professional development. Applicants should hold a PhD and have experience with geospatial environmental data analysis, collaborative programming in Python, and working within distributed teams.