Asks for

The ad says“Build and maintain automated data processing, simulation, and modeling workflows using Linux command-line tools, bash scripting, and Python for both material and cell-level modeling”
The ad says“Leverage standard and advanced characterization methods (BET, TGA, Raman, SEM, XAS, XPS, EPR) alongside computational chemistry tools (DFT, electronic structure modeling via Orca, Gaussian, or Q-Chem, and numerical solvers) to quantify correlations between material properties and electrochemical performance of Li-ion battery active materials and coproducts.”
The ad says“Leverage standard and advanced characterization methods (BET, TGA, Raman, SEM, XAS, XPS, EPR) alongside computational chemistry tools (DFT, electronic structure modeling via Orca, Gaussian, or Q-Chem, and numerical solvers) to quantify correlations between material properties and electrochemical performance of Li-ion battery active materials and coproducts.”
The ad says“Hands-on background in electrochemistry for lithium ion batteries or related field”
The ad says“Leverage standard and advanced characterization methods (BET, TGA, Raman, SEM, XAS, XPS, EPR) alongside computational chemistry tools (DFT, electronic structure modeling via Orca, Gaussian, or Q-Chem, and numerical solvers) to quantify correlations between material properties and electrochemical performance of Li-ion battery active materials and coproducts.”
The ad says“Leverage standard and advanced characterization methods (BET, TGA, Raman, SEM, XAS, XPS, EPR) alongside computational chemistry tools (DFT, electronic structure modeling via Orca, Gaussian, or Q-Chem, and numerical solvers) to quantify correlations between material properties and electrochemical performance of Li-ion battery active materials and coproducts.”
The ad says“Leverage standard and advanced characterization methods (BET, TGA, Raman, SEM, XAS, XPS, EPR) alongside computational chemistry tools (DFT, electronic structure modeling via Orca, Gaussian, or Q-Chem, and numerical solvers) to quantify correlations between material properties and electrochemical performance of Li-ion battery active materials and coproducts.”
The ad says“Build and maintain automated data processing, simulation, and modeling workflows using Linux command-line tools, bash scripting, and Python for both material and cell-level modeling”
The ad says“Leverage standard and advanced characterization methods (BET, TGA, Raman, SEM, XAS, XPS, EPR) alongside computational chemistry tools (DFT, electronic structure modeling via Orca, Gaussian, or Q-Chem, and numerical solvers) to quantify correlations between material properties and electrochemical performance of Li-ion battery active materials and coproducts.”
The ad says“Build and maintain automated data processing, simulation, and modeling workflows using Linux command-line tools, bash scripting, and Python for both material and cell-level modeling”
The ad says“Leverage standard and advanced characterization methods (BET, TGA, Raman, SEM, XAS, XPS, EPR) alongside computational chemistry tools (DFT, electronic structure modeling via Orca, Gaussian, or Q-Chem, and numerical solvers) to quantify correlations between material properties and electrochemical performance of Li-ion battery active materials and coproducts.”
The ad says“Leverage standard and advanced characterization methods (BET, TGA, Raman, SEM, XAS, XPS, EPR) alongside computational chemistry tools (DFT, electronic structure modeling via Orca, Gaussian, or Q-Chem, and numerical solvers) to quantify correlations between material properties and electrochemical performance of Li-ion battery active materials and coproducts.”
The ad says“Leverage standard and advanced characterization methods (BET, TGA, Raman, SEM, XAS, XPS, EPR) alongside computational chemistry tools (DFT, electronic structure modeling via Orca, Gaussian, or Q-Chem, and numerical solvers) to quantify correlations between material properties and electrochemical performance of Li-ion battery active materials and coproducts.”
The ad says“Solid grasp of standard (BET, TGA, Raman, SEM) and advanced spectroscopic/synchrotron techniques (XAS, XPS, EPR) applied to silicon or carbon-based active materials.”
The ad says“Solid grasp of standard (BET, TGA, Raman, SEM) and advanced spectroscopic/synchrotron techniques (XAS, XPS, EPR) applied to silicon or carbon-based active materials.”
The ad says“Leverage standard and advanced characterization methods (BET, TGA, Raman, SEM, XAS, XPS, EPR) alongside computational chemistry tools (DFT, electronic structure modeling via Orca, Gaussian, or Q-Chem, and numerical solvers) to quantify correlations between material properties and electrochemical performance of Li-ion battery active materials and coproducts.”
The ad says“Leverage standard and advanced characterization methods (BET, TGA, Raman, SEM, XAS, XPS, EPR) alongside computational chemistry tools (DFT, electronic structure modeling via Orca, Gaussian, or Q-Chem, and numerical solvers) to quantify correlations between material properties and electrochemical performance of Li-ion battery active materials and coproducts.”
The ad says“Leverage standard and advanced characterization methods (BET, TGA, Raman, SEM, XAS, XPS, EPR) alongside computational chemistry tools (DFT, electronic structure modeling via Orca, Gaussian, or Q-Chem, and numerical solvers) to quantify correlations between material properties and electrochemical performance of Li-ion battery active materials and coproducts.”

About Us

We are Sila, a next-generation battery materials company. Our mission is to power the world’s transition to clean energy. To create this future, our team is building a better lithium-ion battery from the inside out today. We engineer and manufacture ground-breaking battery materials that significantly increase the energy density of batteries, while reducing their size and weight. The result? Smaller more powerful batteries that can unlock innovation in consumer devices and accelerate the mass adoption of electric cars to eliminate our dependence on fossil fuels. We're tackling one of the biggest challenges of our time every day, and together we're redefining what's possible. Are you ready to be a part of a team committed to changing the world?

Who You Are

As an engineer on the RD&E modeling team, you will bridge physical chemistry, advanced characterization, and computational modeling to accelerate the development of high-performance lithium-ion battery materials and cells. You are a cross-functional problem solver who thrives at the intersection of wet-lab characterization and high-performance computing, leveraging advanced models to turn raw empirical and theoretical data into actionable material & cell design rules. Working closely with synthesis, formulation, and commercial teams, you will quantify property-performance relationships for active materials and coproducts to drive technological differentiation.

Responsibilities and Duties

Leverage standard and advanced characterization methods (BET, TGA, Raman, SEM, XAS, XPS, EPR) alongside computational chemistry tools (DFT, electronic structure modeling via Orca, Gaussian, or Q-Chem, and numerical solvers) to quantify correlations between material properties and electrochemical performance of Li-ion battery active materials and coproducts.
Develop and operationalize electrochemical tests at the half and full cell level to extract material-level kinetics and physics for Li-ion active materials.
Build and maintain automated data processing, simulation, and modeling workflows using Linux command-line tools, bash scripting, and Python for both material and cell-level modeling
Translate computational insights into physical material design improvements while guiding internal teams and external customers on cell-level design optimization for maximum power and energy efficiency.
Leverage empirical historical datasets to create model scenarios to inform design opportunities for energy:power differentiation.

Knowledge and Skill Requirements

Ph.D. in Chemistry, Materials Science, Chemical Engineering, or a related physical science discipline.
Deep experience integrating quantum chemistry methods (DFT, electronic structure calculations) with experimental materials characterization
Deep experience in physics based model development and application for lithium ion batteries
High proficiency in Linux environments, CLI tools, bash scripting, Python, and numerical solvers for physical chemistry workflows.
Hands-on background in electrochemistry for lithium ion batteries or related field
Solid grasp of standard (BET, TGA, Raman, SEM) and advanced spectroscopic/synchrotron techniques (XAS, XPS, EPR) applied to silicon or carbon-based active materials.

Physical Demands and Working Conditions

Wear required personal protective equipment (lab coat, safety glasses, gloves, steel-toe shoes) when operating in laboratory environments.
Operate specialized analytical instrumentation, gloveboxes, and computational infrastructure in fixed laboratory and office settings.
Move across facilities and maintain focus during extended computational runs or analytical testing protocols.

The starting base pay for this role is between $172,000 and $218,000 at the time of posting. The actual base pay depends on many factors, such as education, experience, and skills. Base pay is only one part of Sila’s competitive Total Rewards package that can include benefits, perks, equity, and bonuses. The base pay range is subject to change and may be modified in the future.

#LI-PL1 #LI-Onsite

Working at Sila

We believe that building a diverse team at Sila helps us amplify our individual talents. We are an equal opportunity employer and committed to creating an inclusive environment where good ideas are free to come from anyone. We are proud to celebrate diversity and all qualified applicants are considered for employment without regard to gender, race, sexual orientation, religion, age, disability, national origin, or any other status protected by law.