Lead Computational Genomics Scientist – Human Genetics

dawarconsulting; South San Francisco (CA); On-site; USD 151,536,000 - 172,200,000; Full time

Job summary

Our Client in SSF, CA seeks a Computational Scientist - Human Genetics to analyze large-scale genetic and genomic datasets, develop integrative statistical methods, and apply machine learning to connect imaging and omics data. The role involves coordinating data intake, QC, and documenting workflows.

The candidate will work with Human Genetics teams, contributing to publications and translational research initiatives in a long-term contract position.

Qualifications

• PhD or Master’s degree in Statistical Genetics, Computational Biology, Bioinformatics, Genetic Epidemiology, or related field.
• Extensive experience analyzing large-scale genetic/genomic datasets.
• Experience with GWAS and association analysis using human genetic data.
• Experience with RNA-Seq and single-cell/proteomics data.

Responsibilities

• Analyze large-scale genetic, genomic, and clinical datasets from various sources.
• Develop computational and statistical approaches to integrate complex biological data.
• Analyze RNA-Seq, single-cell sequencing, and proteomic data.
• Develop multimodal data integration methods to connect genetic, molecular, and clinical data.
• Apply machine learning to identify associations across datasets.
• Coordinate intake, QC, and organization of new datasets.
• Document workflows, code, methods and findings.
• Present findings to Genetics teams and collaborators.
• Contribute to publications and translational research.

Skills

GWAS analysis

RNA-Seq

Single-cell sequencing

Proteomics data

Genetic epidemiology

Statistical genetics

Data integration

Machine learning

Education

PhD or Master’s in Statistical Genetics / Computational Biology / Bioinformatics

Job description

Our Client in SSF, CA seeks a Computational Scientist - Human Genetics to analyze large-scale genetic and genomic datasets, develop integrative statistical methods, and apply machine learning to connect imaging and omics data. The role involves coordinating data intake, QC, and documenting workflows.

The candidate will work with Human Genetics teams, contributing to publications and translational research initiatives in a long-term contract position.