Charles Watt is a biostatistician with a Master's in Biostatistics and eight years of experience translating complex biomedical data into actionable results across academia and biotech. He consults on study design, grant development, and manuscript preparation while building user-friendly computational tools—like an R package for DIA proteomics—and automated image-analysis pipelines that streamline experimental workflows. Comfortable with R, Python, SAS, and VBA, he has applied advanced PK modeling and NCA in a start-up setting and led MRI and proteomics analyses in university research. Based in Seattle, he blends hands-on statistical programming with pedagogy, developing tailored teaching resources to raise analytic standards among researchers. An uncommon strength is his track record of turning domain-specific problems (soil health pilots to pharmacokinetics) into reproducible, automated pipelines that accelerate discovery.
7 years of coding experience
3 years of employment as a software developer
Master's degree Biostatistics, Master's degree Biostatistics at University of Connecticut
Non-Degree Study Advanced Molecular Biology Laboratory Techniques, Non-Degree Study Advanced Molecular Biology Laboratory Techniques at Yale University
Bachelor of Science and Engineering Chemical and Biological Engineering, Bachelor of Science and Engineering Chemical and Biological Engineering at Princeton University
This program is the JDX file converter that is used to read NIST mass spec data into a CSV format.
Contributions:104 commits in 1 month
masscsvnistspeccsv-format
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