Summary
Sarah Allec is a computational materials scientist and PhD with 9 years of experience applying physics-based modeling, high-throughput screening, and machine learning to design materials and solvents for carbon capture and catalytic applications. Currently a Materials Scientist at Pacific Northwest National Laboratory, she blends DFT and ab initio molecular dynamics with data-driven approaches and production-grade coding in Python and C++ on Linux to move ideas from simulation to actionable insight. Her background includes industry research at Citrine Informatics and a dissertation on predicting amorphous atomic structures, reflecting deep expertise in both fundamental quantum methods and applied informatics. Passionate about democratizing science, she pairs rigorous computation with mentoring and outreach experience, demonstrating an uncommon mix of technical depth and dedication to serving broader communities.
9 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy (PhD), Materials Science & Engineering, Doctor of Philosophy (PhD), Materials Science & Engineering at University of California, Riverside
English