Tech Stack

Description

You will develop algorithms and models to optimize battery performance and safety, leveraging machine learning to accelerate material discovery and improve battery management systems. Your work will directly impact the energy transition by enabling advanced Li-Metal and Li-ion batteries.

Requirements

• MS/PhD in Computer Science, Electrical Engineering, or related field
• Strong background in battery modeling, estimation theory, and control systems
• Proficiency in Python and C/C++ at production level
• Experience with machine learning frameworks (TensorFlow, PyTorch)
• Knowledge of Li-ion and Li-metal battery chemistry and electrochemistry

Responsibilities

• Design and implement battery algorithms for state estimation (SOC, SOH, SOP)
• Develop machine learning models for material discovery and battery performance prediction
• Validate algorithms through simulation, testing, and real-world data analysis
• Collaborate with cross-functional teams to integrate algorithms into battery management systems
• Optimize algorithms for real-time execution on embedded platforms