Senior Computational Geneticist

Tasks

• Analyze human genetics and large scale molecular datasets
• Apply AI assisted approaches to genetics workflows
• Apply genetic and functional genomics to therapeutic target discovery
• Collaborate with AI teams to build AI enabled genetics tools
• Communicate findings to stakeholders and partners
• Conduct causal inference and mechanistic interpretation
• Ensure timely delivery of genetics and genomics data
• Evaluate and validate therapeutic hypotheses
• Integrate genetics with clinical and omics datasets for biomarker discovery
• Manage internal and external collaborations
• Perform quantitative genetics analyses
• Support patient stratification and trial design
• Synthesize literature and generate hypotheses

Perks/Benefits

• 401k plan
• Caregiver parental leave
• Health benefits
• Hybrid work schedule
• Medical leave
• Medical, dental & vision coverage
• Paid Holidays
• Paid personal days
• Paid vacation
• Relocation support

Skills/Tech-stack

AI-assisted research | Artificial Intelligence | Bias Assessment | Bioinformatics | Causal Inference | Computational Biology | Data Analysis | Data bias | Data bias assessment | Data integration | Functional Genomics | Genetic epidemiology | Genomics Data | Genomics data analysis | Language Models | Large Language Models | Machine Learning | Omics Data | Omics data integration | Perl | Population genetics | Python | Quantitative genetics | R | SQL | Statistical Analysis