Bioinformatics Summer Intern

RNA-seq Data Analysis, Bioinformatics Pipelines, Machine Learning, Python, R, Bash Scripting, Linux/Unix, Deep Learning, Large Language Models, NGS Pipelines, Statistics, Data Visualization

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.

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Opportunity to help shape the commercial direction of a novel platform technology

Direct impact on partnerships with leading pharma and diagnostics organizations

Collaborative, science-driven startup environment

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.

40hrs/week, 12 weeks

$35-$42.5/hr

• Analyze RNA-seq datasets, including preprocessing, QC, normalization, and differential expression analysis
• Develop and optimize bioinformatics pipelines for transcriptomic data (bulk RNA-seq and/or degraded RNA samples)
• Apply machine learning and statistical methods to identify diagnostic or predictive biomarkers
• Assist in building and evaluating predictive models, including deep learning approaches
• Explore integration of large language models (LLMs) or multimodal AI approaches for biological data interpretation
• Collaborate with wet-lab scientists and cross-functional teams to interpret results and refine experimental design
• Present findings through reports, visualizations, and internal presentations

• Current PhD student, recent PhD graduate, or postdoctoral researcher in Bioinformatics, Computational Biology, Biology, or a related field
• Hands‑on experience with RNA‑seq data analysis
• Strong programming skills in at least one language (e.g., R or Python)
• Familiarity with Linux/Unix environments and proficiency in bash scripting
• Formal training in statistics and machine learning

• Experience with machine learning frameworks (e.g., scikit‑learn, Tensor Flow, PyTorch)
• Experience building or applying deep learning models
• Familiarity with large language models (LLMs) or generative AI applications in biology
• Experience with NGS pipelines and tools (e.g., STAR, Salmon, nf‑core, etc.)
• Experience working in high‑performance computing (HPC) or cloud environments
• Strong data visualization and communication skills

Hands‑on experience working with cutting‑edge RNA‑seq datasets from clinical samples

Exposure to real‑world biomarker discovery and diagnostic development

Mentorship from experienced scientists in bioinformatics and translational genomics

Opportunity to contribute to impactful healthcare technologies

USD 35 - USD 42.5 - hourly