Computational 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, a world leader in Biotechnology is looking for a "Computational Scientist - Human Genetics" for SSF, CA Job Duration: Long Term Contract (Possibility Of Extension) Pay Rate: $56/hr on W2 Company Benefits: Medical, Paid Sick leave, 401K

Key Responsibilities

• Analyze large-scale genetic, genomic, and clinical datasets from internal studies, clinical trials, high-throughput screens, academic collaborations, industry partners, and public datasets.
• Develop computational and statistical approaches to integrate and interpret complex biological datasets.
• Analyze whole genome sequencing, RNA-Seq, scRNA-Seq, scATAC-Seq, and other molecular assay data.
• Develop and apply multimodal data integration methods to connect genetic, molecular, clinical, and imaging data.
• Implement machine learning algorithms to identify associations between imaging and omics datasets.
• Coordinate the intake, preparation, quality control, and organization of new datasets.
• Document analytical workflows, code, methods, findings, and results.
• Present scientific findings to Human Genetics teams and cross-functional collaborators.
• Contribute to scientific publications and translational research initiatives.

Required Qualifications

• PhD, or Master's degree with significant relevant experience, in Statistical Genetics, Computational Biology, Bioinformatics, Genetic Epidemiology, or a related field.
• Extensive experience analyzing large-scale genetic/genomic datasets.
• Knowledge of genetic epidemiology and statistical genetics.
• Experience with GWAS and association analysis using array- or sequence-based human genetic data.
• Experience analyzing RNA-Seq, single-cell sequencing, and/or proteomic data.