Pay Rate Low: 30 | Pay Rate High: 34

A leading biotechnology research organization is seeking a Junior Computational Biologist to support efforts in refining how cellular states are quantified and validated!

Title: Jr. Computational Biologist (Remote Contract)
Location: Remote (Must be available during PST business hours)
Compensation: $30–34/hour + benefits
Contract Duration: 6–12+ months

Job Duties:
This project will focus on benchmarking functional scoring methodologies and improving interpretability of high-dimensional transcriptomic datasets.
The selected candidate will contribute to distinguishing true biological signal from technical variation in large-scale single-cell atlases, directly enhancing the reliability of automated cell-state classification frameworks.

Start Date: July 1, 2026

• Duration: Through December 18, 2026

• Commitment: Full-time (100%)

• Ideal Candidate: Upcoming June 2026 PhD graduate or recent PhD graduate

• Location: Onsite in South San Francisco, CA preferred; remote within the U.S. considered (must work PST hours)

• Visa Sponsorship: Not availabl

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Key Responsibilities

• Systematically evaluate and benchmark computational approaches for quantifying phenotype activation across single-cell transcriptomic datasets.

• Establish rigorous statistical baselines and negative-control frameworks to improve the robustness of automated cell-state classification methods.

• Develop or refine computational methods to address limitations in current approaches.

• Design strategies to distinguish genuine biological signatures from stochastic or technical noise.

• Present findings in internal scientific reviews and contribute to potential conference abstracts or peer-reviewed publications.

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Required Qualifications

• Extensive hands-on experience in single-cell data analysis using Scanpy, AnnData, and Pandas.

• Strong proficiency implementing statistical and machine learning models using scikit-learn and SciPy.

• Demonstrated commitment to reproducible research practices and well-organized code.

• Ability to clearly communicate complex computational concepts to interdisciplinary scientific teams.

• Master’s degree with ongoing PhD pursuit, or recent PhD graduate, in Computational Biology, Computer Science, Machine Learning, or related quantitative discipline.

• Interest in drug discovery and comfort working in dynamic, research-driven environments.

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Preferred Qualifications

• Background knowledge in cell biology and/or immunology.

• Experience with hypothesis testing, noise modeling, and benchmarking computational tools.

• Familiarity with Explainable AI (XAI) approaches or large-scale biological datasets.

• Demonstrated ability to build or extend novel bioinformatics pipelines.
  
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