PhD position: High-Throughput Development of Chemical Conversion Treatment for Light Metals
Core
Develop and validate experimental methods for accelerated screening of chemical conversion treatment formulations for light metals (Al, Mg) using robotic high-throughput platforms and machine learning.
Role type
PhD researcher in high-throughput materials science and AI-assisted discovery
Builds
Large, machine-readable datasets for AI-assisted discovery of corrosion protection coatings
Domain
Materials science, electrochemistry, corrosion protection, lab automation
Deliverable
production ML models
Required skills
experimental skills in chemical laboratories, quantitative data analysis, experience with corrosion protection and chemical conversion coatings, experience with electronic lab notebooks and FAIR data, curiosity about automation and AI
Preferred skills
knowledge of German language
Technologies
robotic testing platforms, machine learning, electronic lab notebooks
Responsibilities
Develop and validate experimental methods for accelerated screening of chemical conversion treatment formulations; Translate methods into automated high-throughput workflows; Work with computational scientists to build machine-readable datasets; Uncover mechanisms behind adhesion promotion and corrosion protection; Publish results in leading journals and present at international conferences
