Posted Aug 14, 2026

Junior Computational Biologist (Remote)

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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 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. 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. 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. INDBH #LI-MG1