Find & Apply For Biostatistician Jobs in Portland, Oregon

Job Listing ID:

4585921

Job Title:

Research Associate

Application Deadline:

Open Until Filled

Job Location:

Portland

Date Posted:

10/08/2026

Hours Worked Per Week:

40

Shift:

Day Shift

Duration of Job:

Either Full or Part Time, more than 6 months

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Job Summary Research Associate US-OR-Portland Requisition ID:

2026-41981

Position Category:

Research

Job Type:

Research

Position Type:

Regular Full-Time

Posting Department:

SM. Biomedical Engineering

Posting Salary Range:

$53,081

•$88,587 per year, with offer based on experience, education and internal equity

Posting FTE:

1.00

Posting Schedule:

Monday

•Friday, occasional evening/weekends

Posting Hours:

variable, typically 8:30am

•6:00pm

HR Mission:

School of Medicine

Drug Testable:

No Department Overview This position is a member of the Computational Biology Program at OHSU and will work in close collaboration with Dr. Yabing Chen's laboratory on computational studies of atherosclerosis and vascular disease. The position will analyze and integrate single-cell RNA sequencing (scRNA-seq), spatial transcriptomics/spatial omics, bulk transcriptomic, epigenomic, imaging, and related biomedical datasets to define disease-associated cell states, vascular microenvironments, and molecular pathways involved in atherosclerosis. The employee will develop reproducible computational pipelines in R, Python, and Linux; perform quality control, cell-type/state annotation, differential and pathway analyses, spatial and multi-omics integration, and data visualization; and apply statistical, machine-learning, and computational biology methods to generate biologically testable hypotheses. The position will work closely with computational scientists, vascular biologists, and experimental investigators in Dr. Yabing Chen's lab and collaborating groups to translate complex omics data into mechanistic insights, figures, manuscripts, and research proposals. Function/Duties of Position Single-Cell and Spatial Omics Analysis of Atherosclerosis Analyze scRNA-seq and spatial transcriptomics/spatial omics datasets from atherosclerosis and vascular-disease studies.

Perform data quality control, normalization, dimensionality reduction, clustering, cell-type and cell-state annotation, differential expression, pathway analysis, trajectory/state-transition analysis, and spatially resolved characterization of vascular lesions and disease-associated cellular niches. Multi-Omics Integration and Computational Analysis Integrate single-cell and spatial data with bulk RNA-seq, ATAC-seq, imaging, phenotypic, and other relevant datasets.

Apply statistical, machine-learning, network, and multi-omics approaches to identify disease-associated regulatory programs, cell-cell interactions, molecular pathways, and candidate mechanisms relevant to atherosclerosis progression and vascular remodeling. Reproducible Pipelines, Data Engineering, and Visualization Develop, optimize, document, and maintain Equal employment opportunity, including veterans and individuals with disabilities.

PI287539709

Medical Scientists, Except Epidemiologists

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Compensation

Not Provided

Job Requirements

Experience Required:

At least 1 year

Education Required:

High School Diploma/GED

Minimum Age:

N/A