Remote Computational Biologist - Cancer Detection & NGS

Freenome Inc.; Northern (KY); Hybrid; USD 131,000 - 190,000; Full time

Benefits offered by this job

Equity

Bonus opportunities

Medical benefits

Job summary

Freenome Inc. seeks a Computational Biologist to advance the CBAR team’s early cancer detection projects. You will apply quantitative methods to noninvasive tests using cfDNA, designing studies and analyzing molecular and clinical data.

Collaboration with Molecular Research, Model R&D, and Assay Development drives concept feasibility. The role supports hybrid or fully remote work, reports to a Manager/Senior Staff Computational Biologist, and emphasizes development of scalable pipelines and

Qualifications

• PhD required in a quantitative field such as computational biology or related.
• Experience developing high-throughput NGS data pipelines.
• Strong ability to interpret molecular and clinical data for early cancer detection.
• Proficient programming skills in Python (and/or R) and data analysis.
• Excellent written and oral communication for scientific audiences.

Responsibilities

• Lead analysis and interpretation of molecular and clinical data for early cancer detection.
• Propose hypotheses and plan research in collaboration with multidisciplinary teams.
• Develop bioinformatics pipelines for high-throughput NGS data processing.
• Collaborate with wet-lab scientists to iteratively assess assay performance.

Skills

NGS data analysis

Python

R

Data interpretation

Cross-functional collaboration

Education

PhD in computational biology, cancer biology, statistics, bioinformatics

Tools

Python (NumPy, Matplotlib, Pandas)

NGS pipelines

Job description

Freenome Inc. seeks a Computational Biologist to advance the CBAR team’s early cancer detection projects. You will apply quantitative methods to noninvasive tests using cfDNA, designing studies and analyzing molecular and clinical data.

Collaboration with Molecular Research, Model R&D, and Assay Development drives concept feasibility. The role supports hybrid or fully remote work, reports to a Manager/Senior Staff Computational Biologist, and emphasizes development of scalable pipelines and