Company Description
Located in the San Francisco Bay Area, El Capitan Biosciences comprises a team of passionate, versatile, and seasoned professionals. Our team's extensive research and industry backgrounds enable us to stay at the forefront of innovation.
At El Capitan Biosciences (ECB), our mission is to advance noninvasive diagnostics and monitoring by harnessing advanced machine learning algorithms and proprietary molecular methods to extract, quantify and interpret human RNA present in stool. By enabling whole transcriptome-sequencing of human transcripts shed from gut and immune cell populations, we aim to discover clinically meaningful biomarkers that reflect mucosal integrity, presence of disease, inflammatory activity and broader gastrointestinal health. Our multiplex RNA-based panels integrate signals across multiple pathways to deliver a comprehensive, actionable picture of disease biology, supporting improved diagnosis, monitoring, and overall understanding of gut health.
Company website: https://elcapitanbio.com/
Why Join Us
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Opportunity to help shape the commercial direction of a novel platform technology
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Direct impact on partnerships with leading pharma and diagnostics organizations
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Collaborative, science-driven startup environment
Job Description
Position Overview
We are seeking a highly motivated Bioinformatics Summer Intern to support the development of RNA-seq data analysis pipelines and machine learning models for biomarker discovery and clinical diagnostics. This role is ideal for candidates interested in translational genomics, AI in healthcare, and next-generation diagnostics.
Schedule: 40hrs/week, 12 weeks
Hourly rate: $35-$42.5/hr
Key Responsibilities
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Analyze RNA-seq datasets, including preprocessing, QC, normalization, and differential expression analysis
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Develop and optimize bioinformatics pipelines for transcriptomic data (bulk RNA-seq and/or degraded RNA samples)
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Apply machine learning and statistical methods to identify diagnostic or predictive biomarkers
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Assist in building and evaluating predictive models, including deep learning approaches
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Explore integration of large language models (LLMs) or multimodal AI approaches for biological data interpretation
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Collaborate with wet-lab scientists and cross-functional teams to interpret results and refine experimental design
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Present findings through reports, visualizations, and internal presentations
Qualifications
Basic Qualifications
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Current PhD student, recent PhD graduate, or postdoctoral researcher in Bioinformatics, Computational Biology, Biology, or a related field
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Hands-on experience with RNA-seq data analysis
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Strong programming skills in at least one language (e.g., R or Python)
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Familiarity with Linux/Unix environments and proficiency in bash scripting
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Formal training in statistics and machine learning
Preferred Qualifications
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Experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch)
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Experience building or applying deep learning models
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Familiarity with large language models (LLMs) or generative AI applications in biology
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Experience with NGS pipelines and tools (e.g., STAR, Salmon, nf-core, etc.)
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Experience working in high-performance computing (HPC) or cloud environments
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Strong data visualization and communication skills
Additional Information
What You’ll Gain
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Hands-on experience working with cutting-edge RNA-seq datasets from clinical samples
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Exposure to real-world biomarker discovery and diagnostic development
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Mentorship from experienced scientists in bioinformatics and translational genomics
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Opportunity to contribute to impactful healthcare technologies
