PhD Position: AI-driven computational models for battery degradation
Core
Develop AI-driven computational models and multi-scale simulations to predict battery degradation and accelerate ultra-fast charging technology.
Role type
PhD researcher (Research Scientist)
Builds
Digital Twin for predictive ultra-fast charging
Domain
Energy / Battery Technology / Computational Physics
Deliverable
production ML models
Required skills
Machine Learning, Model Order Reduction (MOR), multi-physics simulation, electro-chemistry modeling, numerical methods, Bayesian optimization, active learning
Preferred skills
experience with numerical modelling, background in mechanical engineering
Technologies
ML frameworks, PDE solvers, simulation tools
Responsibilities
Develop physics-based coupled electro-chemical and mechanical models for batteries; Investigate degradation phenomena for specific chemistries; Develop workflows linking physics-based models to ML-accelerated ROM; Evaluate and validate numerical models against experimental data; Disseminate findings via publications and conferences.
Seniority
PhD Candidate
