Internship: e-Hydrogen Cost Optimizer (Future development)
King Abdullah University of Science and Technology (KAUST)
Saudi Arabia
Summary
Enhance a Python decision-support tool for electrolytic hydrogen with advanced techno-economic optimization, scalable MILP models, expanded electrolyser technology coverage, comprehensive LCA sustainability metrics, and interactive scenario and policy simulation interfaces.
