Key Qualifications General understanding of Li-ion battery modeling. Knowledge of detailed battery modeling and electrochemistry is a plus. Knowledge of battery cell design and materials would also be a plus. Proficient in using modeling and simulation tools like MATLAB, Simulink and other specialized tools. Experience in writing efficient codes to analyze large data sets. Familiarity with Git and code review process. Attention to details and ability to develop high quality code documentation. Experience in dynamic modeling, statistical and machine learning algorithm design. Experience of developing solutions using control theories like Kalman filters, state observers. Experience in mathematical modeling of linear and nonlinear dynamical systems and distributed parameter systems. Experience solving optimization problems. Expertise in C/C++ programming is a plus. Description In this position you will be expected to use a combination of advanced mathematics, machine learning, electrical engineering, and control engineering knowledge to: Develop advanced battery models and control algorithms to improve battery performance. Develop models to estimate and optimize cell and pack performance in design phase. Analyze large volumes of test data to understand cell performance differences and propose design improvements to address them. Develop algorithms to estimate State of charge and State of Power of batteries. Develop machine learning algorithms or mathematical models to predict cell performance across life. Develop simulation models and tools to evaluate such new algorithms. Education Degree in engineering or mathematics/physics related discipline and direct experience in similar role required. MS with 3+ years of related experience or PhD with relevant experience preferred. As an equal opportunity employer, ICONMA provides an employment environment that supports and encourages the abilities of all persons without regard to race, color, religion, gender, sexual orientation, gender identity or express, ethnicity, national origin, age, disability status, political affiliation, genetics, marital status, protected veteran status, or any other characteristic protected by federal, state, or local laws