Senior Statistical Geneticist: Cardio Genomics & AI

Cytokinetics; San Francisco (CA); Vor Ort; USD 185.000 - 215.000; Vollzeit

Benefits dieser Stelle

Stock options

Health, dental, vision, life insurance

401k with employer match

Learning stipends

Paid time off

Zusammenfassung

Cytokinetics is seeking a highly motivated statistical geneticist to discover and evaluate therapeutic targets for cardiac and skeletal muscle diseases. You will lead analyses of large biobanks, develop AI/ML-based phenotypes from EHR/imaging, and apply fine-mapping and Mendelian randomization to identify causal genes.

Collaboration with experimental teams and publication of findings are key responsibilities.

Qualifikationen

• PhD in Statistical Genetics, Human Genetics, Bioinformatics or related field with 4+ years post-doctoral or industry experience.
• Strong expertise analyzing large-scale genomic datasets, including GWAS and sequencing data.
• Experience translating genetic associations into candidate therapeutic hypotheses or targets.

Aufgaben

• Perform GWAS and sequencing association studies across biobanks to discover and replicate associations.
• Develop quantitative and longitudinal phenotypes from EHR and imaging using AI/ML methods.
• Apply fine-mapping, colocalization, Mendelian randomization and burden methods to identify causal genes.
• Prioritize targets using genetic evidence for efficacy and safety and collaborate with experimental teams.
• Build reproducible pipelines and present findings internally and at conferences.

Kenntnisse

Statistical genetics

R

Python

GWAS

MR methods

Biobank analysis

Colocalization

Fine-mapping

AI/ML

Data analysis

Communication

Ausbildung

PhD in Statistical Genetics

Tools

R

Python

AWS

UKB RAP

All of Us Workbench

Jobbeschreibung

Cytokinetics is seeking a highly motivated statistical geneticist to discover and evaluate therapeutic targets for cardiac and skeletal muscle diseases. You will lead analyses of large biobanks, develop AI/ML-based phenotypes from EHR/imaging, and apply fine-mapping and Mendelian randomization to identify causal genes.

Collaboration with experimental teams and publication of findings are key responsibilities.