Clayton Curtis
Postdoctoral Researcher at Sandia National Laboratories
Albuquerque, New Mexico, United States
Summary
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Senior🎓
Top SchoolClayton Curtis is a postdoctoral researcher at Sandia National Laboratories with over a decade of hands-on experience in chemical synthesis and materials characterization, focused on stimuli-responsive materials, chemical sensors, and tamper-indicating technologies. He earned his PhD and MS in Chemistry from the University of Arizona after undergraduate work at Manchester University, where early research on carbon-based nanoparticles informed his electrochemical expertise. Clayton combines advanced spectroscopic and electrochemical techniques (UV-vis, SC-XRD, EPR, NMR, cyclic voltammetry) to connect molecular design with functional device behavior, particularly exploring redox-active ligand systems and supramolecular interactions. Known for thriving in fast-paced, mission-driven environments, he bridges fundamental inorganic chemistry with applied materials solutions for national-lab scale challenges. An understated strength is his ability to translate nuanced ligand-electronic structure relationships into practical sensing and tamper-detection strategies.
9 years of coding experience
6 years of employment as a software developer
The University of ArizonaBachelor of Science - BS, Chemistry, Bachelor of Science - BS, Chemistry at Manchester University
Github Skills (66)
causal10
assembly10
probabilistic9
probabilistic-models9
nlp8
extraction8
machine-learning8
natural-language-processing8
ccl7
latex7
mathematics7
mathjax7
tsne7
biomedical7
typography7
Programming languages (11)
Github contributions (5)
ml4ai/nli4wills-corpus
Oct 2022 - Nov 2022
Legal Will Statements for Natural Language Inference
Contributions:31 commits, 27 pushes, 1 branch in 14 days
corpus-linguisticslawlinguisticsnatural-language-processingnlp
ml4ai/automates-v2
Jun 2020 - Jan 2023
AutoMATES: Automated Model Assembly from Text, Equations and Software
Contributions:2 reviews, 351 commits, 44 PRs in 2 years 8 months
automatesequationsassemblymachine-learning
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