Research Scientist, Accelerated Materials Design and Discovery
Los Altos, CA; Cambridge, MA /
Materials Discovery – Accelerated Materials Design and Discovery /
At Toyota Research Institute (TRI), we’re working to build a future where everyone has the freedom to move, engage, and explore with a focus on reducing vehicle collisions, injuries, and fatalities. Join us in our mission to improve the quality of human life through advances in artificial intelligence, automated driving, robotics, and materials science. We’re dedicated to building a world of “mobility for all” where everyone, regardless of age or ability, can live in harmony with technology to enjoy a better life.
We strive to build a company that helps our people thrive, achieve work-life balance, and bring their best selves to work. At TRI, you will have the opportunity to enjoy the best of both worlds ‒ a fun environment with forward-thinking people who enjoy solving tough problems and the financial backing to successfully achieve our goals. Come work with TRI if you’re interested in transforming mobility through designing technology for safer cars, enabling the elderly to age in place, or designing alternative fuel sources. Start your impossible with us.
The long-term vision of TRI’s Accelerated Materials Design and Discovery (AMDD) program is to accelerate the development of truly emissions-free mobility. Realizing this vision will require the discovery of new materials and devices for batteries, fuel cells, and more. Our aim at TRI is to merge sophisticated computational materials modeling, new experimental data, artificial intelligence, and automation to significantly accelerate materials research in this area. Our focus is on developing tools and capability to enable this acceleration. In addition to the research work of the internal team, we collaborate closely with a dozen universities and national labs. AMDD seeks to develop and translate the newest technologies into practice, both within Toyota and the open research community more broadly.
We are looking for a research scientist who can help us develop innovative approaches to accelerate materials discovery and their experimental realization. Right now, we need help with analysis of data from high-throughput catalysis experiments. You will develop new machine learning models that incorporate scientific theory or intuition. You will collaborate with software engineers to translate your research into prototype tools that can be used by the wider community. We all get opportunities to start new seedling projects that are focused on prototyping new innovative approaches. We regularly get to present our work at conferences and within the Toyota family of companies, patent our innovations, and publish papers in high impact journals.
We encourage you to join a creative team of a dozen scientists and engineers dedicated to enabling a sustainable future. We all grow working alongside other inspiring people, and constantly learn new skills together at the interface of materials science and AI. You will combine your individual research with the rest of the teams’ and our collaborators’. Together with our collaborators, we have early access to comprehensive data streams and the capabilities we develop provide them feedback to optimize their scientific workflows. We have a high degree of autonomy which gives us the privilege to select challenges to address, play to our strengths and pursue the solutions we believe in.
We are currently working from home, but when we get back in the office you can be working in our headquarters in Los Altos, or in our Cambridge office following a shorter stay in HQ.
We'd love to hear from you if you:
- Have a PhD in physics, chemistry, chemical engineering, materials science, applied mathematics/computer science, or a related field.
- Have a strong research background, including peer-reviewed publications.
- Are proficient at a general-purpose programming language (preferably Python) or R.
- Have effective written and verbal communication skills.
- Have demonstrated interest in machine learning.
- Have experience with or want to learn practices for team-based software development.
- Thrive in a culture that values diversity, collaboration, humility, and learning.
It’s a bonus if you:
- Have experience with analyzing electrochemical/spectral/time-series data.
- Have experience with designing databases for scientific workflows.
- Have experience with a common deep learning framework.
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