Intern - Battery Diagnostics

Responsibilities

• Support the development of SOX (SOC, SOH, etc.) estimation algorithms for LFP-based Battery Energy Storage Systems (BESS)
• Support the testing and validation of SOX algorithms from Model-in-the-Loop (MIL) to Hardware-in-the-Loop (HIL)
• Analyze large-scale BMS field data to identify degradation signatures, sensor anomalies, and operational outliers
• Perform quantitative analysis to investigate the impact of cell-level and system-level parameters on state estimation accuracy and battery lifetime

Requirements

• Currently enrolled in an MSc or PhD program in a quantitative discipline (e.g., Battery Technology, Electrical Engineering, Chemical Engineering, Physics, or Computer Science)
• Strong knowledge of lithium-ion battery electrochemistry and degradation mechanisms, ideally with LFP experience
• Experience with battery state estimation algorithms such as Coulomb counting, OCV-based methods, Kalman filters, or equivalent circuit models
• Proficiency in programming languages such as Python, Matlab, C++, or C
• Fluency in written and spoken English

Preferred Qualifications

• Knowledge in state estimation, battery modeling, or data-driven modeling
• Experience with BMS algorithm testing
• Working knowledge of Chinese or German

Benefits

• Access to a global network for intensive knowledge and experience exchange
• Diverse and welcoming work environment with approximately 40 different nationalities
• Broad range of training opportunities, including online and face-to-face programs and language courses
• On-site company canteen offering a variety of meal options

About the Company

Huawei is a leading global information and communications technology (ICT) solutions provider. The Huawei Ohm Research Center in Nuremberg focuses on advanced technology research and strategic planning, specifically within the Digital Power business unit to support the European energy transition through green and efficient power electronics.