Linnea Honeker Hernandez
Postdoctoral Researcher @Lawrence Livermore National Laboratory
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WORK HISTORY
Postdoctoral Researcher @Lawrence Livermore National Laboratory
Livermore, CA, US
Apply bioinformatics tools to unravel patterns of microbial ecology, diversity, and activity with a focus on discovery of microbial functional traits that predict ecosystem fluxes and services, such as soil carbon storage.
EDUCATION
University of Arizona
Bachelor of Science (BS), Ecology and Evolutionary Biology
University of Arizona
Doctor of Philosophy (PhD), Environmental Science, Minor in Microbiology
ABOUT LINNEA HONEKER HERNANDEZ
I am a data-driven scientist and bioinformatics specialist with expertise in analyzing complex biological and environmental datasets to generate actionable insights. My work sits at the intersection of microbiology, biogeochemistry, and data science, where I develop and apply analytical workflows to understand how biological systems respond to environmental change. Across my career, I have built and integrated large, high-dimensional datasets (e.g, multi-omics, environmental measurements, and isotope tracing data) using Python, R, and Bash. I specialize in data quality assessment, dataset integration, statistical analysis, and translating complex outputs into clear reports, visualizations, and recommendations for diverse stakeholders. In my current role at Lawrence Livermore National Laboratory, I develop scalable data analysis pipelines to quantify microbial impacts on carbon cycling and ecosystem processes. This includes working across interdisciplinary teams to connect data, improve analytical workflows, and support data-driven decision-making in complex research environments. I bring strong experience in: Data analysis and modeling (Python, R) Data integration and quality troubleshooting across complex datasets Building reproducible workflows (Git, Docker) Communicating insights through reports, visualizations, and presentations Collaborating with cross-functional teams and mentoring analysts I am particularly interested in applying my analytical and problem-solving skills to real-world challenges in data-driven environments, including agriculture, biotechnology, and environmental systems.
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