Job Description
About the position
The Senior Scientist in Computational Biology at Takeda will play a crucial role in supporting clinical-stage portfolios, focusing on biomarker discovery and biomarker-driven early clinical studies for immune and inflammatory diseases. This position involves applying advanced bioinformatics and AI/ML strategies to analyze multi-omic data, contributing to the development of innovative analytical strategies and supporting decision-making in early-stage clinical trials. The role requires collaboration with various stakeholders and may involve managing early-stage project teams.
- Responsibilities
- Leverage high-dimensional datasets, including multi-omics data, to discover biomarkers and stratify patients. ,
- Perform data integration and network/pathway analysis to understand mechanisms of action. ,
- Apply AI/ML tools and generative AI models for biomarker discovery and integrate findings with existing knowledge. ,
- Prepare and present technical and scientific reports for internal and external audiences. ,
- Collaborate closely with project teams to influence experimental design and data analysis. ,
- Participate in due diligence for external opportunities as needed. ,
- Independently design and execute research projects in collaboration with translational scientists.
- Requirements
- PhD in Computational Biology or Bioinformatics with 3+ years post-doctoral experience, or MS with 9+ years experience, or BS with 11+ years experience. ,
- Strong background in multi-omics biomarker analysis. ,
- Experience with proteomics, single-cell and spatial transcriptomics or spatial high-content imaging data is preferred. ,
- Knowledge of drug development and experience in a matrix team environment. ,
- Experience with AI/ML, statistical analysis, including regression analysis, multivariate data analysis, and mixed-effects modeling is preferred. ,
- Proficiency in Unix/Linux, command line interfaces, and scripting/programming languages (R, Python) for multi-omics analysis. ,
- Proficient in developing data strategies and integrating multi-omic and genome-wide datasets. ,
- Experienced in large-scale omics, high-throughput data analysis, network analysis, meta-analyses and AI/ML models for translational research.
- Nice-to-haves
- Experience with AI/ML tools and generative AI models for biomarker discovery. ,
- Experience in managing early-stage matrix project teams.
- Benefits
- Medical, dental, and vision insurance ,
- 401(k) plan with company match ,
- Short-term and long-term disability coverage ,
- Basic life insurance ,
- Tuition reimbursement program ,
- Paid volunteer time off ,
- Company holidays ,
- Well-being benefits ,
- Sick time and paid vacation accrual
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