Research Engineer: Self-Driving Materials Discovery

Robert Bosch Group; Watertown (MA); On-site; USD 140,000 - 160,000; Full time

Job summary

Robert Bosch Group in Watertown, MA, seeks a Research Engineer to advance computational materials science for next‑generation Bosch products. You will apply atomistic and AI techniques, work with experimental teams, and contribute to cross‑disciplinary research in HMI, robotics, energy, and electronics.

The role requires a PhD in a related field, strong Python programming, and experience with HPC environments and machine learning applied to materials science.

Qualifications

• PhD in materials science, chemistry, physics, chemical/ mechanical engineering, biophysics, or closely related field.
• Hands-on experience with atomistic simulation and computational materials science.
• Proficiency in programming and the scientific Python ecosystem.
• Experience applying AI/machine learning to scientific problems.
• Ability to conduct independent research and communicate results.

Responsibilities

• Conduct applied research in atomistic materials science using rigorous physical principles.
• Apply conventional methods and AI tools to derive actionable insights and validate models.
• Collaborate with external partners and internal teams.
• Disseminate results via publications, reports, presentations, and IP disclosures.
• Build an AI-based framework enabling engineers to apply atomistic simulation to practical problems.

Skills

Python (scientific)

Independent research

Communication skills

High-performance computing

Education

PhD in materials science or related field

Tools

Python tools for science

HPC environments

Job description

Robert Bosch Group in Watertown, MA, seeks a Research Engineer to advance computational materials science for next‑generation Bosch products. You will apply atomistic and AI techniques, work with experimental teams, and contribute to cross‑disciplinary research in HMI, robotics, energy, and electronics.

The role requires a PhD in a related field, strong Python programming, and experience with HPC environments and machine learning applied to materials science.