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Key Responsibilities
Develop and maintain scalable data pipelines and tools to deliver clean, reliable battery datasets, supporting model development and control algorithm research. Aggregate, curate, and normalize design-phase cell and pack data to enable accurate estimation and optimization analyses. Ingest and process large volumes of lab and field test data; implement robust data quality checks and feature extraction to quantify cell performance differences and inform design improvements. Build labeled datasets and feature stores, and prepare model-ready datasets for machine learning training and algorithm validation. Ensure synchronization, validation, and traceability of ground-truth signals. Develop and run simulation workflows to validate models and produce performance projections, including scenario generation, parameter sweeps, and results tracking. Required Skills
Battery modeling and algorithm knowledge (20%) Hands-on experience in data analysis (20%) Proficiency in Matlab programming (20%) Experience with C/Python is a plus (10%) Familiarity with machine learning, optimization, and control algorithms is a plus (10%) Degree in Data Science, Electrical Engineering, Computer Science, Chemical Engineering, or Mechanical Engineering is preferred (20%)
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Compétences linguistiques
- English
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