Postdoctoral Fellow: Biomedical Informatics & Multimodal ML

Jobtailor; Seattle (WA); On-site; USD 120,000 - 180,000; Full time

Job summary

Jobtailor seeks a highly qualified Biomedical Informatics researcher to lead experiments from design through first-authored publications. The role focuses on developing and validating machine learning and statistical methods to enhance clinical decision support and uncover disease mechanisms.

The candidate will perform multimodal analyses on genomic, phenomic and exposome data and collaborate with ISB colleagues and nationwide teams, contributing to cutting-edge interdisciplinary research.

Qualifications

• PhD in Biomedical Informatics or related field required.
• First authorship on one published, peer-reviewed article.
• Expertise in developing and validating machine learning models on biomedical data.
• Experience with multimodal modeling for clinical decision support or disease mechanisms.

Responsibilities

• Own biomedical informatics experiments from design through first-authorship publications.
• Develop and validate machine learning and statistical processes to improve clinical decision support or insights into disease mechanisms.
• Conduct multimodal modeling on high-dimensional longitudinal genomic, phenomic and exposome data.
• Collaborate on research projects with colleagues at ISB and nationwide.

Skills

Machine Learning

Statistical Processes

Data Preparation

Model Validation

Biomedical Data Analysis

Genomic Data Analysis

Phenomic Data Analysis

Exposome Data Analysis

Generative Models

Modeling And Analysis Methods

Education

PhD in Biomedical Informatics / related field

Job description

Jobtailor seeks a highly qualified Biomedical Informatics researcher to lead experiments from design through first-authored publications. The role focuses on developing and validating machine learning and statistical methods to enhance clinical decision support and uncover disease mechanisms.

The candidate will perform multimodal analyses on genomic, phenomic and exposome data and collaborate with ISB colleagues and nationwide teams, contributing to cutting-edge interdisciplinary research.