Bioinformatics/Data Scientist
Conduct multi-omics analyses (scRNA-seq, bulk RNA-seq, proteomics, metabolomics) on organoid systems to characterize fidelity and identify biomarkers. Develop computational pipelines, integrate public datasets, and collaborate with experimental teams. Requires a PhD in bioinformatics or related field with strong R/Python skills.
About the job
Responsibilities
- Analyze complex datasets including single-cell RNA sequencing, bulk RNA sequencing, proteomics, and metabolomics data from various organoid systems and their tissue counterparts.
- Develop and implement computational pipelines for data processing, quality control, and statistical analysis.
- Integrate SOM-generated data with publicly available datasets to benchmark organoid characteristics against normal tissue profiles.
- Collaborate with experimental teams to interpret results and guide protocol optimization.
- Contribute to manuscript preparation and present findings at scientific conferences.
Requirements
- PhD in bioinformatics, computational biology, biostatistics, or a related quantitative field.
- Extensive experience with single-cell data analysis, including familiarity with tools such as Seurat, Scanpy, or similar platforms.
- Strong programming skills in R and Python.
- Experience in statistical analysis and data visualization.
- Knowledge of proteomics and metabolomics data analysis workflows.
Nice-to-Haves
- Previous 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.
Skills
R, Python, Seurat, Scanpy, Single-Cell Rna Sequencing, Bulk Rna Sequencing, Proteomics Data Analysis, Metabolomics Data Analysis, Statistical Analysis, Data Visualization, Machine Learning, High-Performance Computing
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