The Knight Cardiovascular Institute (KCVI) is recognized as a top integrated center for cardiovascular clinical care, translational research and professional training in all aspects of heart and vascular disease. Guided by a multi-disciplinary approach, researchers and clinicians drive a vibrant translational research program, which focuses on delivering the latest knowledge and cutting-edge care to patients. Specifically, research at KCVI seeks to improve patient outcomes by achieving earlier diagnosis of disease, more accurate monitoring of its progression, and tailoring therapy to the molecular basis of disease.

 

The Cardiomyopathy Section within the Knight Cardiovascular Institute (KCVI) seeks a Computational Biologist 1 to support translational and clinical research focused on hypertrophic cardiomyopathy, infiltrative cardiomyopathies (e.g., amyloidosis), dilated cardiomyopathy, and related heart failure phenotypes. Working under supervision, the Computational Biologist will develop and apply computational, statistical, and data-analytical methods to extract biological and clinical insights from complex datasets, including next‑generation sequencing (NGS) and other omics data, imaging-derived features, and curated clinical/EHR and clinical trial datasets. The position will assist cardiomyopathy investigators and study teams by implementing reproducible, scalable analysis workflows; maintaining well-documented code and data products; and translating results into clear visualizations and summaries for multidisciplinary audiences. The Computational Biologist will contribute to manuscript and grant development, and will collaborate closely with clinical research staff to ensure appropriate handling of protected health information (PHI) and adherence to institutional, sponsor, and regulatory requirements for research data.

• Computational Workflow Development & Reproducibility
  
  • Implement and maintain scalable, reproducible computational workflows for cardiomyopathy research (e.g., bulk/single‑cell RNA-seq, WGS/WES, proteomics) using best practices (version control, containerization, documentation).
  • Assist platform or study teams with workflow execution on institutional compute resources and/or cloud environments.
  • Contribute to open, reusable code where appropriate and support internal documentation/user guides.
• Data Processing, Quality Control & Statistical Analysis
  
  • Process, curate, and harmonize multi‑modal datasets (omics, imaging metrics, phenotypic and clinical trial data).
  • Apply sound statistical methods and modeling approaches to investigate genotype‑phenotype associations, biomarker discovery, and outcome prediction under guidance.
  • Generate clear data visualizations and interpretable summaries for investigators and study teams. 
• Data Management, Governance & Compliance Support
  
  • Work with clinical research staff to ensure secure handling of PHI and compliant storage/sharing of datasets (IRB, HIPAA, sponsor/data use agreements).
  • Develop and maintain analysis-ready datasets, metadata, and data dictionaries; assist with building/maintaining databases or trackers used by the team.
  • Support documentation needed for audits, reproducibility, and data provenance (e.g., analysis logs, code notebooks, QC reports). 
• Research Collaboration & Scientific Communication
  
  • Meet with cardiomyopathy investigators, clinicians, and research staff to clarify analysis questions, define deliverables, and communicate results.
  • Provide guidance to non-computational staff on study design considerations for data-generating experiments (e.g., sequencing depth, batch effects) within scope and under supervision. 
• Academic Output & Professional Development
  
  • Contribute to manuscripts, abstracts, posters, presentations, and grant applications (bioinformatics/quantitative sections) with review by senior staff.
  • Maintain current awareness of relevant computational biology methods and cardiomyopathy literature; participate in lab/section meetings and training opportunities. 

• Master’s Degree in Computational Biology or related field OR
• Bachelor’s degree in computational biology or related filed AND 3 years of experience 
• Experience conducting and assisting with computational analysis of high‑dimensional biological data (e.g., NGS/omics). 
• Proficiency in R and/or Python for data processing, analysis, and visualization.
• Familiarity with common bioinformatics file formats and QC approaches.
• Ability to implement workflows/pipelines using best practices (version control, documentation).
• Strong written and oral communication skills; ability to explain analyses to non-computational colleagues.
• Strong organizational skills, attention to detail, and ability to manage priorities under supervision.
• Ability to perform the job duties with or without accommodation.

• Master’s Degree with cardiology/cardiovascular focus
• Experience with cardiology/cardiomyopathy datasets, EHR/clinical trial data integration, and scalable workflow execution (HPC/cloud).
• Familiarity with cardiomyopathy biology and/or cardiac genetics.
• Experience with single‑cell analysis frameworks, variant annotation, and multi‑omics integration.
• Experience contributing to open-source software or shared analysis libraries.
• Experience with data governance, de-identification, and secure research computing.

We are Oregon's only public academic health center.

In addition to caring for patients, we lead groundbreaking research. We also train the next generation of health care professionals. As Portland's largest employer, we give you opportunities to learn and advance in a system of hospitals and clinics across Oregon and Southwest Washington.

All are welcome.

OHSU welcomes people of all ages, ethnicities, genders, national origins, religions and sexual orientations. We are striving to build an anti-racist, multicultural institution and encourage people with diverse backgrounds to apply.

To request reasonable accommodation, contact askhr@ohsu.edu