Battery Modeling Engineer

A123 Systems; Novi (MI); On-site; USD 75,000 - 95,000; Full time

Job summary

A123 Systems is seeking a Battery Modeling Engineer in Novi, Michigan. The role involves developing physics-based models for battery chemistry, optimizing designs, and creating machine learning models for manufacturing processes.

Applicants should have a Ph.D. in Engineering or a related field, and knowledge in electrochemical modeling, machine learning, and software programming is required. Join A123 and contribute towards cleaner air solutions.

Qualifications

• Strong knowledge of electrochemical modeling and battery aging.
• Solid understanding of battery chemistry and manufacturing processes.
• Experience in machine learning and data cleaning.

Responsibilities

• Develop physics-based models to identify aging mechanisms and optimize cell design.
• Develop data-driven AI models to enhance battery manufacturing processes.
• Conduct life simulations for various battery systems.

Skills

Electrochemical modeling

Battery aging knowledge

Machine learning

Modeling of electrochemical systems

Software skills (COMSOL, Matlab, Python)

Experience with ML libraries (Tensor Flow, PyTorch)

Education

Ph.D. degree in Engineering, Physics, Math, or Statistics

Job description

A123 Systems, LLC is a leading developer and manufacturer of advanced lithium-ion battery technologies and energy storage systems. Our solutions serve a wide range of applications, from traditional automotive batteries to utility-scale and commercial & industrial (C&I) energy storage. Committed to safety, longevity, and energy efficiency, A123 delivers high-performance battery technology solutions with a strong commitment to grow and serve our customers, industry requirements with the goal to make the Air Cleaner.

Position Overview

The Advanced Simulation Technology & AI Department at A123 Systems is hiring a Battery Modeling Engineer with the major responsibilities of developing physics-based models for different cell chemistry to understand the aging mechanisms and optimize the cell design, and developing data-driven AI machine learning models to optimize battery cell manufacturing process. Other responsibilities include conducting cell-, module-, and pack-level life simulation for Li-ion battery systems used in electric vehicles, plug-in hybrid electric vehicles, hybrid electric vehicles, energy storage systems, drone and electric vertical take-off and landing.

Primary Responsibilities

• Develop physics-based models to identify aging mechanisms and optimize cell design.
• Develop data-driven AI machine learning models to optimize the design of battery cell manufacturing process considering the cell quality control and capital costs.
• Support NBO and regular life simulation activities through global collaboration.
• Work in a global team and collaborate with cross-functional team colleagues.
• Communicate findings to external customers in a positive and constructive manner, and establish/maintain technical communications for any open issues.

Specific Skills / Experience

• Solid knowledge of electrochemical modeling and battery aging.
• Solid Knowledge of battery chemistry and battery manufacturing.
• Excellent experience in modeling of electrochemical systems.
• Solid knowledge of machine learning, data cleaning, cloud computing, etc.
• Sophisticated software/programming skills, such as COMSOL, Matlab, Python, etc.
• Experience with ML libraries, i.e., Tensor Flow, PyTorch, etc.
• Experience in Li-ion battery modeling and machine learning in industry is a plus.
• Strongly self-motivated and willingness to learn new knowledge.
• 0-2 years industry working experience.

Education

• Ph.D. degree in Engineering, Physics, Math, Statistics, Analytics, etc.