About the Job
Key responsibilities:1. Analyze large datasets from Li-Ion battery testing, including data from Incremental Capacity Analysis (ICA), Differential Voltage Analysis (DVA), Electrochemical Impedance Spectroscopy (EIS), and long-term cycling studies
2. Develop and implement machine learning models (supervised and unsupervised) to predict battery State-of-Health (SoH), State-of-Charge (SoC), and Remaining Useful Life (RUL)
3. Integrate physics-based models (e.g., equivalent circuit models, electrochemical models) with machine learning approaches for hybrid diagnostics and prognostics
4. Extract and engineer diagnostic features from raw battery data to identify degradation patterns and failure modes
5. Collaborate with hardware and embedded teams to integrate diagnostic algorithms into embedded platforms and cloud-based analytics tools
6. Visualize and communicate complex data insights effectively through dashboards, reports, and presentations
7. Stay updated with the latest research in battery diagnostics, degradation modeling, and advanced analytics.
Number of Openings
1 openingsPerks of this Jobs
Free snacks Informal dress code
Skills
Deep Learning, Model Evaluation, CNN (Convolutional Neural Network), RNN (Recurrent Neural Network), PyTorch, Battery Management Systems, Data Analysis, Amazon Web Services (AWS), Data Visualization, Simulink, Computer Vision, Machine Learning, Python, Algorithms, MATLAB, Model fine-tuning, Data Engineering, Plotly, Keras
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