Multi-Omics Data Scientist Fellow

Axle; Rockville (MD); On-site; USD 90,000 - 100,000; Full time

Benefits offered by this job

Paid Time Off

401K match up to 5%

Educational Benefits

Employee Referral Bonus

FSA

Parking Reimbursement Account

Dependent Care Assistant Program

Transportation Reimbursement Account

Job summary

Axle in Rockville, MD invites applications for the Bioinformatics Fellow for Multi-Omics Analysis. The role will analyze multi-omics data from organoid systems, assess organoid fidelity, and identify biomarkers of differentiation while developing computational frameworks for quality assessment.

You will implement pipelines for data processing, integrate single-cell and omics data, and collaborate with experimental teams to refine protocols.

Qualifications

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

Responsibilities

• Multi-omics analysis of single-cell RNA-seq, bulk RNA-seq, proteomics, and metabolomics.
• Develop pipelines for data processing, QC, and statistical analysis.
• Benchmark organoid data against normal tissue profiles.
• Develop methods for classifying cellular states and organoid quality.
• Collaborate with experimental teams and other computational staff.
• Contribute to manuscripts and conference presentations.

Skills

Single-cell analysis

Omics workflows

R programming

Python programming

Education

PhD in bioinformatics / related field

Tools

Seurat

Scanpy

HPC

Git

Job description

Axle in Rockville, MD invites applications for the Bioinformatics Fellow for Multi-Omics Analysis. The role will analyze multi-omics data from organoid systems, assess organoid fidelity, and identify biomarkers of differentiation while developing computational frameworks for quality assessment.

You will implement pipelines for data processing, integrate single-cell and omics data, and collaborate with experimental teams to refine protocols.