Automated MD Simulations for Ionomers Intern @ Toyota Research Institute

At Toyota Research Institute (TRI), we’re on a mission to improve the quality of human life. We’re developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we’ve built a world-class team in Robotics, Human-Centered AI, Human Interactive Driving, and Energy & Materials.

This is a Summer 2024 paid 12-week internship opportunity. Please note that this internship will be a hybrid in-office role.

The Team

The Energy and Materials Division at TRI is building tools to accelerate the design and discovery of new materials, fostering a transition to more sustainable mobility. Our research applies AI, data-driven methods, and automation to materials science, and spans the atomic to the device scales. Our projects often involve collaboration with scientists from universities and national labs. Interns will be involved in industrial research on topics of broader interest to the general materials science community, and several previous intern projects have resulted in peer-reviewed publications in journals such as npj Computational Materials and Chemical Science.

The Internship

The goal of the High Throughput Polymer Design (HTP) project is to accelerate the design of new polymers for zero emissions technology using high throughput experimental and computational methods. We previously developed a Molecular Dynamics (MD) simulation workflow to model ion transport in solid, amorphous homopolymer electrolytes, and have demonstrated this for the closed-loop design of new polymer electrolytes.

In the next phase, we are looking to extend our automated MD framework to explore the ionomer candidates for the next generation of fuel cells. This will help us to have a deeper understanding of proton transport and copolymer design. The daily responsibilities in this role will include developing and refining MD simulation workflows, implementing benchmark simulations, and validating the results by comparing them with the experimental data.

Qualifications

Currently enrolled in a doctoral program in materials science, polymer science, mechanical engineering, chemical engineering, chemistry, physics, computer science, or other related fields
Experienced in coding with Python
Have experience with molecular dynamics simulations using LAMMPS

Bonus Qualifications

Experience with modeling polymers, copolymers, and ionomers
Experience in using MedeA software, and polymer consistent force field (PCFF+)
Demonstrated interest in machine learning

Please add a link to Google Scholar and include a full list of publications when submitting your CV to this position.

The pay range for this position at commencement of employment is expected to be between $45 and $65/hour for California-based roles; however, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. Note that TRI offers a generous benefits package including vacation and sick time. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.

Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information.

TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant’s race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws.

Compensation Overview

Qualifications

Bonus Qualifications

6 month growth

1 year growth

2 year growth

Benefits