Computational Biologist: Multi-Omic Risk & Biobank Insights

MyOme; Menlo Park (CA); Hybrid; USD 130,000 - 150,000; Full time

Benefits offered by this job

Equity

Job summary

MyOme is seeking a driven Computational Biology Scientist to leverage large-scale biobank data for multi-omic disease risk prediction. You will work at the intersection of observational epidemiology, high-throughput omics, and statistical modeling to identify signatures that predict risk before clinical onset.

You will collaborate with computational scientists, assay scientists, clinical and regulatory experts, and product teams to prioritize targets for experimental validation, while advancing

Qualifications

• Ph.D. in Computational Biology, Bioinformatics, Biostatistics, Epidemiology, Human Genetics, or related quantitative field with 0–4 years (or Master’s with 3–6+ years).
• Hands-on experience querying and analyzing multi-modal data in major cohorts (UK Biobank or All of Us).
• Experience analyzing two or more data types (proteomics, metabolomics, methylation, transcriptomics).
• Strong observational study design, association testing, confounding control, and time-to-event modeling.

Responsibilities

• Ingest and QC large-scale public biobank data with emphasis on UK Biobank and All of Us.
• Analyze multi-omics data including proteomics, metabolomics, methylation, and transcriptomics.
• Apply biostatistical and ML methods to evaluate phenotype associations and early disease risk.
• Design fast computational experiments to test incremental predictive value of multi-omic panels.
• Collaborate with cross-functional teams to prioritize targets for validation.

Skills

Biobank data mining

Multi-Omics analysis

Risk prediction

Observational epidemiology

Biostatistics

Machine learning

Python

R

Git

Cloud platforms

Education

Ph.D. in Computational Biology

Tools

Python

R

Git

DNAnexus

Terra

AWS

GCP

Job description

MyOme is seeking a driven Computational Biology Scientist to leverage large-scale biobank data for multi-omic disease risk prediction. You will work at the intersection of observational epidemiology, high-throughput omics, and statistical modeling to identify signatures that predict risk before clinical onset.

You will collaborate with computational scientists, assay scientists, clinical and regulatory experts, and product teams to prioritize targets for experimental validation, while advancing