Bioinformatics Scientist: Multi-Omics & Organoid Analytics

Axle; United States; Remote; USD 105,000 - 120,000; Full time

Benefits offered by this job

PTO & holidays

401K match

Educational benefits

Employee referral bonus

Flexible Spending Accounts

Job summary

Axle in the United States seeks a Bioinformatics / Data Scientist to lead multi-omics analyses from organoid systems and matched tissues, focusing on organoid fidelity and biomarkers of successful differentiation.

You will develop computational pipelines in R and Python, apply scRNA-seq, proteomics and metabolomics, design experiments with wet-lab teams, benchmark against public datasets, and contribute to manuscript preparation and conferences.

Qualifications

• Doctoral degree in bioinformatics, computational biology, biostatistics, or related quantitative field.
• Extensive experience with single-cell data analysis using tools like Seurat or Scanpy.
• Strong programming in R and Python, with statistical analysis and data visualization skills.
• Basic knowledge of proteomics and metabolomics data.

Responsibilities

• Multi-omics analysis of single-cell RNA sequencing, bulk RNA sequencing, proteomics and metabolomics data from organoid systems and tissue counterparts.
• Experimental design consultation with wet-lab teams to optimize protocols for discovery and performance.
• Develop and implement computational pipelines for data processing, QC and statistical analysis.
• Benchmark organoid characteristics against public datasets to assess fidelity.
• Collaborate with experimental teams to interpret results and guide protocol optimization.
• Contribute to manuscript preparation and present findings at scientific conferences.

Skills

Single-cell analysis

R & Python

Bioinformatics

Education

PhD in bioinformatics or related field

Tools

Seurat

Scanpy

Job description

Axle in the United States seeks a Bioinformatics / Data Scientist to lead multi-omics analyses from organoid systems and matched tissues, focusing on organoid fidelity and biomarkers of successful differentiation.

You will develop computational pipelines in R and Python, apply scRNA-seq, proteomics and metabolomics, design experiments with wet-lab teams, benchmark against public datasets, and contribute to manuscript preparation and conferences.