Research Engineer, Accelerated Materials Discovery & AI

Energy Jobline ZR; Watertown (MA); On-site; USD 140,000 - 160,000; Full time

Job summary

Bosch Corporate Research in Watertown, MA seeks a Research Engineer to conduct applied computational materials science at the atomistic level and contribute to next-generation Bosch products. You will use classical and AI-powered simulations to move concepts quickly from idea to quantitative models, aligning with engineering cycles and experimental campaigns.

The role requires engaging with experimental efforts, collaborating across industry, labs and academia, and communicating complex results

Qualifications

• PhD in materials science, chemistry, physics, chemical engineering, mechanical engineering, biophysics or a closely related field.
• Experience with atomistic simulation and computational materials science.
• Proficiency in programming with Python or equivalent computational tools.
• Experience applying AI/machine learning techniques to scientific problems.
• Ability to conduct independent research, including formulating research questions, analyzing data, and developing prototypes.

Responsibilities

• Conduct applied research in materials science rooted in physical and chemical principles at the atomistic level.
• Apply atomistic methods and AI tools to derive insights on materials behavior and optimization.
• Identify, connect, and work with external collaborators.
• Communicate results through internal reports, publications, and IP disclosures.
• Contribute to an interdisciplinary research environment across materials science, physics, chemistry, AI, and software.
• Create AI-based frameworks enabling Bosch engineers to apply atomistic simulation to complex materials.

Skills

Atomistic simulation

AI/ML in science

Python

HPC

Education

PhD in related field

Job description

Bosch Corporate Research in Watertown, MA seeks a Research Engineer to conduct applied computational materials science at the atomistic level and contribute to next-generation Bosch products. You will use classical and AI-powered simulations to move concepts quickly from idea to quantitative models, aligning with engineering cycles and experimental campaigns.

The role requires engaging with experimental efforts, collaborating across industry, labs and academia, and communicating complex results