Description

In this internship, you will dive into advanced battery system modeling, focusing on algorithm development and testing. Your responsibilities will include analyzing data, developing machine learning models, and collaborating with R&D teams to drive project success.

Requirements

• •Master’s or PhD degree in Electrical Engineering, Chemical Engineering, Energy Systems, Battery Technology, Data Science, or related field
• •Basic understanding of battery systems, energy storage technologies, or electrochemical principles
• •Strong interest in battery modeling, state estimation (SoC/SoH), and degradation mechanisms
• •Hands-on experience with Python or R for scientific computing and data analytics
• •Strong analytical mindset and willingness to learn data analysis methods
• •Good communication and teamwork skills to collaborate in a multidisciplinary environment
• •Fluency in written and spoken English

Tasks

• •Assist in developing battery algorithms focused on state estimation
• •Support modeling battery behavior using Equivalent Circuit Models
• •Preprocess and analyze experimental and field datasets
• •Visualize datasets to ensure high-quality input for models
• •Develop machine learning models for SoC/SoH estimation
• •Implement statistical models for degradation prediction
• •Create models for anomaly detection
• •Simulate and benchmark algorithms in Python or similar environments
• •Contribute to technical documentation and reports
• •Summarize methods, results, and insights in presentations
• •Collaborate with R&D teams to align on project milestones

Tools & Technologies

Benefits