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AxleAxleFrederick, MD

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.

105k – 120k
On-siteEntry levelData Science

About the role

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

RPythonSeuratScanpySingle-Cell Rna SequencingBulk Rna SequencingProteomics Data AnalysisMetabolomics Data AnalysisStatistical AnalysisData VisualizationMachine LearningHigh-Performance Computing

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