Data Scientist Fellow — Multi-Omics Analysis
About The Position
The Bioinformatics Fellow for Multi-Omics Analysis will conduct comprehensive analyses of multi-omics data generated from organoid systems and corresponding normal tissues. The Fellow will characterize organoid fidelity, identify biomarkers of successful differentiation, and develop computational frameworks for organoid quality assessment. The role also provides substantive training in integrative analysis of single-cell and multi-omics data. This work supports the SOM Center’s research objectives and is intended to prepare the Fellow for an independent research career in academia, government, or industry. The position involves analyzing datasets from organoid systems and tissue counterparts, developing reproducible computational pipelines, benchmarking organoids against normal tissue profiles, refining analytical methods, collaborating with experimental and computational teams, and contributing to the dissemination of research findings.
Requirements
- Doctoral degree (PhD) in bioinformatics, computational biology, biostatistics, or a related quantitative field, completed or anticipated before the appointment starts.
- Extensive experience with single-cell data analysis, including familiarity with Seurat, Scanpy, or comparable platforms.
- Strong programming proficiency in R and Python.
- Experience in statistical analysis and data visualization.
- Working knowledge of proteomics and metabolomics data analysis workflows.
Nice To Haves
- Prior experience analyzing organoid datasets.
- Experience with machine learning approaches for biological data.
- Familiarity with pathway analysis tools.
- Knowledge of developmental biology principles.
- Experience with high-performance computing environments and version control systems.
Responsibilities
- Analyze complex datasets, including single-cell RNA sequencing, bulk RNA sequencing, proteomics, and metabolomics data from organoid systems and their tissue counterparts.
- Develop and implement computational pipelines for data processing, quality control, and statistical analysis, and document them to support reproducibility across the Center.
- Integrate Center-generated data with publicly available datasets to benchmark organoid characteristics against normal tissue profiles.
- Develop and refine analytical approaches, including machine learning methods where appropriate, for classifying cellular states and assessing organoid quality.
- Contribute to standardized organoid assessment protocols.
- Work with experimental teams to interpret results and guide protocol optimization.
- Collaborate with computational staff on cross-modality data integration.
- Contribute to manuscript preparation and present findings at scientific conferences.
Benefits
- 100% medical, dental, and vision coverage for employees.
- Paid time off and paid holidays.
- 401(k) match up to 5%.
- Educational benefits for career growth.
- Employee referral bonus.
- Flexible spending accounts for healthcare (FSA), parking reimbursement (PRK), dependent care (DCAP), and transportation reimbursement (TRN).
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree
