Research Engineer – Battery Material Modeling

Jobtailor; Dearborn (MO); On-site; USD 90,000 - 130,000; Full time

Job summary

Jobtailor seeks a highly skilled battery materials modeler to develop predictive models of Li-ion battery cathode materials. You will integrate data from synthesis and characterization to drive mechanistic insight into degradation and performance, collaborating across teams to translate modeling into real materials and devices.

Applicants should hold a Master and preferably a PhD in related fields, with hands-on experience in DFT/ML/AI/MD and lab-scale material synthesis or processing.

Qualifications

• Master's degree in materials science, engineering, chemistry, or related field.
• 3 years of experience in chemical and physical modeling of Li-ion battery materials, especially cathode, using DFT/ML/AI/MD.
• Laboratory experimental skills in synthesizing and/or processing battery materials, performing cell testing and advanced material characterization methods.
• Fundamental understanding of chemical processes and mechanisms within batteries from formation to end of life.
• PhD in battery materials science, engineering, chemistry or related fields.

Responsibilities

• Develop models based on target material properties including density, fast ionic diffusion, composition, phase stability, etc.
• Provide actionable mechanistic insight into function and degradation processes in battery cells, including phase evolution, interfacial layer formation and growth, and electrolyte additive function.
• Take data inputs from material and battery synthesis and characterization.
• Collaborate with other team members to implement the modeled insights and learnings in real battery materials and systems.
• Participate in joint projects with universities and national labs that leverage DFT/ML/AI/MD and other modeling methods.

Skills

DFT modeling

ML/AI modeling

Battery materials analysis

Data interpretation

Education

Master's degree in materials science or related

PhD in battery materials science or related

Tools

DFT software

Laboratory equipment

Job description

Responsibilities

• Develop models based on target material properties including density, fast ionic diffusion, composition, phase stability, etc.
• Provide actionable mechanistic insight into function and degradation processes in battery cells, including phase evolution, interfacial layer formation and growth, and electrolyte additive function.
• Take data inputs from material and battery synthesis and characterization.
• Collaborate with other team members to implement the modeled insights and learnings in real battery materials and systems.
• Participate in joint projects with universities and national labs that leverage DFT/ML/AI/MD and other modeling methods.

Requirements

• Master’s degree in materials science, engineering, chemistry, or related fields.
• 3 years of experience in chemical and physical modeling of Li-ion battery materials, especially cathode, using DFT/ML/AI/MD.
• Laboratory experimental skills in synthesizing and/or processing battery materials, performing cell testing and advanced material characterization methods.
• Fundamental understanding of chemical processes and mechanisms within batteries from formation to end of life.
• Doctorate (PhD) in battery materials science, engineering, chemistry or related fields.
• Experience with modeling, testing and characterizing Na-ion batteries is a plus.
• A wide range of material analysis experience is also desirable. This may include teardown and post-mortem analysis of materials from pouch, cylindrical, and/or prismatic.
• A track record of written and/or oral presentations of research findings to specialist or non-specialist audiences.