Matthew Evans
Leverhulme Trust Early Career Research Fellow at datalab industries ltd.
King's Lynn and West Norfolk, England, United Kingdom
Summary
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Rockstar🎓
Top SchoolMatthew Evans is a research-focused software engineer and Leverhulme Trust Early Career Research Fellow with 11 years’ experience building open-source infrastructure for materials chemistry and research data management. He directs datalab-industries and has driven RDM platforms like datalab and the OPTIMADE standard, improving interoperability across major materials databases and contributing backend work to high-profile projects such as pymatgen. His background blends hands-on development of tools for high-throughput materials discovery and ML (MODNet, active learning workflows) with applied experimental support and teaching at Cambridge. Notably, he combines academic rigor from a Cambridge PhD with product-minded consulting, regularly shipping tested, typed Python code and automated tests to make materials data more discoverable and reusable.
10 years of coding experience
9 years of employment as a software developer
MPhys, Physics with Theoretical Physics, First class (Hons), MPhys, Physics with Theoretical Physics, First class (Hons) at The University of ManchesterDoctor of Philosophy (Ph.D.), Condensed Matter and Materials Physics, Doctor of Philosophy (Ph.D.), Condensed Matter and Materials Physics at University of Cambridge
Github Skills (7)
material-design10
science10
python10
materials-informatics10
computational-materials-science10
apidoc9
api9
Programming languages (16)
Github contributions (5)
materialsproject/pymatgen
Sep 2021 - Nov 2021
Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.
Role in this project:
Back-end Developer & Test Automation Engineer
Back-end Developer & Test Automation EngineerContributions:6 reviews, 5 commits, 14 PRs in 2 months
Contributions summary:Matthew primarily contributed to the `pymatgen` library by enhancing its OPTIMADE integration. Their work involved removing incorrect parameters, adding tests to validate OPTIMADE filter functionality, adding type hints for improved code clarity, and incorporating the ability to request additional fields from OPTIMADE APIs. Furthermore, the user addressed code formatting inconsistencies and corrected errors in filter construction and URL generation, contributing to improved data retrieval.
moleculespythonscienceelectronic-structurepowers
datatractor/yard
Apr 2024 - Mar 2025
Place for all of your data extractors!
Contributions:7 releases, 10 reviews, 24 PRs in 11 months
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