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About the Role
This role is part of the Life Sciences team, working on challenges spanning the therapeutic development cycle, including discovering and validating therapeutic targets and developing patient stratification strategies. The Scientist is an early-career member of the team who will thrive in a highly collaborative environment. With the team’s support, you will develop and execute innovative scientific approaches and effectively communicate findings to stakeholders.
Responsibilities
- Generate novel therapeutic hypotheses for diseases with unmet need by mining in-house data resources using statistical approaches.
- Understand the causal pathophysiology of disease, identify and triage potential targets with genetic evidence.
- Build a rich understanding of cell types, cellular function, tissue-level characteristics, patient populations, and biomarkers to support a development program.
- Apply and optimize risk tools for patient stratification that combine genetic information with conventional risk factors.
- Identify individuals most at risk of disease onset or progression and those most likely to benefit from particular therapies.
Requirements
- Strong foundation in the application of statistical and computational techniques in biomedical science.
- Ability to analyze vast and diverse sources of ‘omic data using leading statistical or AI/ML approaches.
- Ability to effectively share findings with others.
- Solid foundations in Statistics (modelling, regression).
- Solid foundations in Genetics and molecular biology.
- Solid foundations in Statistical programming (e.g., Python or R).
- Experience using a broad array of statistical genetics approaches (e.g., GWAS, colocalization, fine-mapping, Mendelian randomization, polygenic risk scores).
- Experience defining phenotypes from electronic health records.
- Knowledge of Bayesian inference, high dimensional statistics, causal inference.
- Experience with software engineering practices (version control [Git & GitHub], testing, documentation, agentic coding, containerisation).
- Experience building and running reproducible pipelines (e.g., using WDL, Snakemake, or NextFlow).
- Experience using cloud computing and trusted research environments (e.g., DNAnexus or Verily Workbench).
- Experience with methods development within statistical genetics.
Skills
- Statistical modelling
- Regression analysis
- Genetics
- Molecular biology
- Python
- R
- GWAS
- Colocalization
- Fine-mapping
- Mendelian randomization
- Polygenic risk scores
- Electronic health records
- Bayesian inference
- High dimensional statistics
- Causal inference
- Git
- GitHub
- WDL
- Snakemake
- NextFlow
- DNAnexus
- Verily Workbench
Location
- RTP
Work Type
- Hybrid
Experience Level
- Early-career
Salary/Compensations
- Competitive Salary: Salaries are externally benchmarked annually to ensure top-of-market compensation.
Benefits
- Clear Career Path: A straightforward, open progression framework.
- Continuous Learning: Including external courses and a wide library of L&D materials.
- PTO: 25 days vacation, plus 8 federal holidays, plus an extra 3-day company-wide shutdown at year-end.
- Full Coverage: 401k, Comprehensive Health, Dental, and Vision plans, Health Savings Account (HSA), Life/AD&D, and Disability coverage.
- Flexible Working: Hybrid Working.
- Truly Inclusive Time Off: 'Bank Your Bank Holiday' program allows you to exchange public holidays for dates that hold personal or cultural significance.
- Vibrant Social Culture: Regular Town Halls, team picnics, organised sports events.
About the Company
- Genomics is a science-led transatlantic TechBio combining large-scale genetic and health data with proprietary analytics to accelerate drug discovery and advance predictive, preventative healthcare.
- The company's vision is to help people live longer, healthier lives using the power of genomics.
- Genomics aims to help people live longer, healthier lives by super-charging drug discovery and development for novel treatments with its AI-enabled advanced genetic analytics platform.
- Genomics also helps people understand their personal risk of common chronic diseases through polygenic risk scores, giving doctors and health systems the chance to get the right people into the right prevention, screening and treatment programmes at the right time.
Equal Opportunity
- All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.