Senior Cell Modeling & Analytics Engineer

Peak Energy•Broomfield, CO

19h•Hybrid

About The Position

Peak Energy is seeking a Senior Cell Modeling & Analytics Engineer to develop the predictive models and data analytics that drive cell design, performance optimization, and life prediction for sodium-ion cells. The ideal candidate brings a deep understanding of battery failure mechanisms and applies that expertise across thermal and heat-generation modeling, equivalent circuit modeling, physics-based electrochemical modeling, and 3D battery modeling. In this role you will build models that predict battery life, characterize thermal behavior, and optimize performance, and you will analyze large sets of cell performance data to surface trends, anomalies, and optimization opportunities. The successful candidate combines strong modeling and simulation skills with rigorous data analysis to create models that drive innovation and efficiency across our battery-powered products.

Requirements

Bachelor's or Master's degree in Engineering, Chemistry, Materials Science, Data Science, Computer Science, or a related field.
Minimum of 5 years of hands-on experience in battery modeling and battery data analysis.
Deep understanding of lithium-ion and/or sodium-ion battery technologies, including their failure mechanisms.
Hands-on experience with cell modeling approaches spanning thermal / heat-generation modeling, equivalent circuit modeling, and physics-based electrochemical modeling.
Proficiency in programming languages such as Python, with experience in data manipulation, physical modeling, statistical modeling, and machine learning.
Experience working with large datasets, performing statistical analysis, and using data visualization tools.
Strong problem-solving skills and the ability to interpret and analyze complex datasets.

Nice To Haves

PhD degree in Engineering, Chemistry, Materials Science, Data Science, Computer Science, or a related field.
Experience in the simulation of battery materials, electrodes, and cells.
Knowledge of electrochemical models and battery simulation tools (e.g., COMSOL, GT-AutoLion, PyBaMM, Simulink).
Experience developing 3D battery models for coupled electrochemical-thermal-mechanical simulation.
Experience in advanced battery data analysis, such as dQ/dV fitting and EIS modeling.

Responsibilities

Develop, validate, and refine battery life models to predict cell life and performance under various operating conditions.
Develop thermal and heat-generation models at the cell level to characterize temperature distribution, heat rejection, and thermal behavior under operating and abuse conditions, and to inform cell and system thermal design.
Build and parameterize equivalent circuit models (ECMs) for cell performance prediction, state estimation (SOC/SOH), and integration into system-level and BMS simulations.
Develop physics-based models (e.g., electrochemical / pseudo-2D / Doyle-Fuller-Newman) to capture the underlying transport, kinetics, and degradation mechanisms that govern cell behavior and guide design decisions.
Build 3D battery models to simulate spatially resolved electrochemical, thermal, and mechanical behavior across cell geometries and formats.
Analyze large sets of battery performance data to identify trends, anomalies, and optimization opportunities and assess model accuracy.
Collaborate with cross-functional teams, including cell engineers and ESS engineers, to integrate battery data and models into broader product-level models and enhance battery performance in the ESS product.
Build and implement algorithms for advanced data analysis, using tools like Python.
Create and maintain comprehensive reports, visualizations, and dashboards to communicate findings and recommendations.
Assist in root-cause analysis on battery failures and contribute to improving product design and performance.
Continuously research advancements in battery technologies, modeling methods, and data science methodologies to improve current processes.