Axle is seeking a Bioinformatics/Data Scientist to support the Standardized Organoid Model Center at the NIH. The role focuses on analyzing multi-omics data from organoid systems to characterize organoid fidelity, identify biomarkers, and develop computational frameworks for quality assessment, ultimately advancing organoid research.
Requirements
- Extensive experience with single-cell data analysis, including familiarity with tools such as Seurat, Scanpy, or similar platforms, is essential.
- Strong programming skills in R and Python are required, along with experience in statistical analysis and data visualization.
- Knowledge of proteomics and metabolomics data analysis workflows is necessary.
- Experience with machine learning approaches for biological data, familiarity with pathway analysis tools, and knowledge of developmental biology principles will be considered valuable assets.
- Experience with high-performance computing environments and version control systems is desirable.
Responsibilities
- The successful candidate will analyze complex datasets including single-cell RNA sequencing, bulk RNA sequencing, proteomics, and metabolomics data from various organoid systems and their tissue counterparts.
- The position will develop and implement computational pipelines for data processing, quality control, and statistical analysis.
- A major component of the role involves integrating SOM-generated data with publicly available datasets to benchmark organoid characteristics against normal tissue profiles.
- The position requires close collaboration with experimental teams to interpret results and guide protocol optimization, as well as contributing to manuscript preparation and presenting findings at scientific conferences.
Other
- Candidates must hold a PhD in bioinformatics, computational biology, biostatistics, or a related quantitative field.
- Previous experience analyzing organoid datasets is strongly preferred.
