Perform genome-wide association studies (GWAS), fine-mapping, and other statistical genetics analyses using large-scale genomic datasets (e.g., UK Biobank, All of Us, FinnGen, etc.).
Analyze and integrate multi-omics data (genomics, transcriptomics, proteomics, metabolomics) to identify causal variants and pathways associated with cardiovascular diseases.
Develop and apply statistical models to predict disease risk and treatment response based on genetic and clinical data.
Design and evaluate AI/ML methods for large-scale imaging-derived phenotyping (e.g., cardiac MRI, DEXA)
Conduct Mendelian randomization studies to infer causal relationships between genetic variants and cardiovascular traits.
Target Identification and Validation:
Identify and prioritize genetic targets for therapeutic intervention based on statistical and functional evidence.
Contribute to the design and analysis of genetic studies to validate drug targets and biomarkers.
Collaborate with experimental biologists and clinicians to translate genetic findings into preclinical and clinical research.
Bioinformatics and Data Management:
Develop and maintain bioinformatics pipelines for processing and analyzing genomic and electronic health records (EHR) data.
Manage and curate large-scale genetic and clinical datasets.
Utilize and develop statistical software and tools for data analysis and visualization (e.g., R, Python, PLINK, Hail).
Collaboration and Communication:
Collaborate with cross-functional teams, including biologists, clinicians, and computational scientists.
Present research findings at internal meetings, scientific conferences, and in peer-reviewed publications.
Contribute to the preparation of regulatory documents and grant applications.
Maintain detailed and organized records of all analyses.
Requirements
Education: Ph.D. in Statistical Genetics, Human Genetics, Bioinformatics, Computational Biology or a related field with
6+ years of experience in the biotech or pharmaceutical industry (or relevant post-doctoral experience) and demonstrated impact on project progression
Strong expertise in analyzing large-scale genomic datasets, including GWAS and sequencing data.
Proficiency in statistical programming languages (R, Python) and bioinformatics tools.
Experience with Mendelian randomization and multi-omics data integration is highly desirable.
Prior experience in the cardiovascular / cardiometabolic therapeutic domain is strongly preferred.
Strong analytical and problem-solving skills.
Excellent communication and presentation skills.
Ability to work independently and as part of a team.
Strong organizational and time management skills.
Ability to learn new skills quickly.
Experience with cloud computing platforms (e.g., AWS, Google Cloud) and biobank research analysis platforms (e.g., DNAnexus RAP, All of Us Workbench)
Experience with machine learning and deep learning methods, and strong interest in applying these methods to biological problems
Experience with multidimensional and longitudinal data analysis in biology or medicine
Publications in peer-reviewed journals related to statistical genetics and cardiovascular disease.
Please submit your CV, a cover letter outlining your research experience and interests, and a list of publications
#LI-ONSITE
Pay Range:
Our employees come from different backgrounds, and we celebrate those differences. We are looking for the best candidates for our open roles, but do not expect applicants to meet every qualification in order to be considered. If you are excited about what you could accomplish a
Benefits
Health insurancePaid time offEquity / stock options
Additional Information
Cytokinetics is a specialty cardiovascular biopharmaceutical company, building on its over 25 years of pioneering scientific innovations in muscle biology, and advancing a pipeline of potential new medicines for patients suffering from diseases of cardiac muscle dysfunction.
At Cytokinetics, each team member plays an integral part in advancing our mission to improve the lives of patients. We are seeking tenacious, compassionate, and collaborative individuals who are driven to make a positive impact.
We are seeking a highly motivated and skilled Principal Scientist, Translational Genetics to join our growing team. The successful candidate will play a critical role in analyzing large-scale genetic and genomic datasets to identify and select therapeutic targets for cardiovascular and muscle diseases. This position requires a strong foundation in statistical genetics, bioinformatics, AI/ML methods, genomics and a passion for translating genetic insights into clinical applications.
Cytokinetics · South San Francisco, CA