Organoid Bioinformatics Data Scientist

Axle Labs; Frederick (MD); On-site; USD 105,000 - 120,000; Full time

Benefits offered by this job

Medical, dental & vision coverage

Paid time off & holidays

401K match up to 5%

Educational benefits

Employee referral bonus

FSA: Healthcare

Parking reimbursement

Dependent Care Assistant Program

Transportation reimbursement

Job summary

Axle Labs is seeking a Bioinformatics/Data Scientist to join the NIH SOM Center in Frederick, MD. The role focuses on analyzing multi-omics data from organoid systems and normal tissues to characterize organoid fidelity and identify biomarkers of successful differentiation.

The candidate will build computational pipelines, integrate datasets, and collaborate with experimental teams, contributing to manuscripts and conferences.

Qualifications

• PhD in bioinformatics, computational biology, biostatistics, or related field.
• Extensive experience with single-cell data analysis using Seurat, Scanpy or similar tools.
• Strong programming skills in R and Python; experience in statistics and data visualization.
• Knowledge of proteomics and metabolomics data analysis workflows.

Responsibilities

• Analyze multi-omics data from organoid systems and normal tissues to assess organoid fidelity and biomarkers of differentiation.
• Develop and implement computational pipelines for data processing, QC, and statistical analysis.
• Integrate SOM-generated data with public datasets to benchmark against normal tissue profiles.
• Collaborate with experimental teams to interpret results and contribute to manuscripts and conferences.

Skills

Single-cell data analysis

R programming

Python programming

Statistical analysis

Data visualization

Education

PhD in bioinformatics / computational biology / biostatistics

Tools

Seurat

Scanpy

Job description

Axle Labs is seeking a Bioinformatics/Data Scientist to join the NIH SOM Center in Frederick, MD. The role focuses on analyzing multi-omics data from organoid systems and normal tissues to characterize organoid fidelity and identify biomarkers of successful differentiation.

The candidate will build computational pipelines, integrate datasets, and collaborate with experimental teams, contributing to manuscripts and conferences.