SUMMARY: At SUNCAT, we are seeking a highly qualified candidates to work on New methods in Computational Electrochemistry. Candidates with advanced programing skills (python,SQL and javascript) and high accuracy ab-initio specialists (including beyond DFT such as QMC) are encouraged to apply.
KEYWORDS: Computational Electrochemistry, DFT, QMC, python,SQL and javascript, databases
DESCRITION: The position, which is funded under the core SUNCAT funding for at least 2 years (based on yearly basis), involes method developement and extensive implementation (python coding) of new electochemical methods that can describe ground and trasition state properties at the Catalysts-electrolyte inteface. The researcher will have a opprtunity to fully integrate the electrochemistry with our python workflow and data storage at the Catalysis-hub.org. ML acceleration, experiment-theory collabs and beyond DFT will be strongly encouraged. Further opportunities within Stanford and SLAC-DOE are also possible in a long term.
CONTACTS: Please contact MIchal Bajdich (bajdich@stanford.edu) for application and position details.