Postdoctoral Fellow: Rare Disease Privacy & Data Science

UNC-Chapel Hill; Chapel Hill (NC); On-site; USD 60,000 - 75,000; Full time

Benefits offered by this job

Medical coverage

Vision coverage

Paid leave

Job summary

UNC-Chapel Hill seeks a Postdoctoral Research Associate to develop methods for defining rare disease cohort controls and assessing re-identification risk across EHR, claims, registry, and linked data. You will build frameworks for privacy risk factors unique to rare conditions and model risks from external sources.

You will design disclosure controls, collaborate with patient groups and IRBs, and contribute to practical guidance that protects patients while preserving scientific value.

Qualifications

• Experience with statistical disclosure control, privacy-preserving data methods, or re-identification risk assessment.
• Experience in R or Python for statistical modeling and analysis of large health datasets.
• Experience working with sensitive health data (EHR, claims, registry) and completion of human subjects training.

Responsibilities

• Investigate methods for defining rare disease cohort controls and assessing re-identification risk in diverse data sources.
• Design and evaluate creation of control populations for small, rare disease groups where traditional methods may not apply.
• Develop disclosure controls (ontology-based aggregation, suppression, enclaves, federated analysis) and assess impact on data utility.
• Engage with patient advocacy groups, data stewards, and IRBs to align research with governance.

Skills

Statistical disclosure control

R or Python

Handling sensitive health data

Human subjects training

Distributed team collaboration

Education

PhD in biostatistics, statistics, epidemiology, biomedical informatics, computer science, or related field

Job description

UNC-Chapel Hill seeks a Postdoctoral Research Associate to develop methods for defining rare disease cohort controls and assessing re-identification risk across EHR, claims, registry, and linked data. You will build frameworks for privacy risk factors unique to rare conditions and model risks from external sources.

You will design disclosure controls, collaborate with patient groups and IRBs, and contribute to practical guidance that protects patients while preserving scientific value.