Research Engineer at BoschGroup

Seniority in posting: entry

Compensation

$140,000 – $160,000/yr

Setup: Hybrid
Location: Watertown, Massachusetts
Type: Full-time
Level: senior
Posted: Sep 10, 2026

Description

Bosch Corporate Research is hiring a Research Engineer to conduct applied computational materials science research at the atomistic level. The role combines classical and electronic structure simulations, machine learning, high-performance computing, and experimental collaboration to develop materials insights and AI-based simulation frameworks for Bosch products. Candidates need a relevant PhD, demonstrated atomistic simulation and AI/ML research experience, programming expertise, and a record of research impact.

Required Skills

Atomistic simulation
Density functional theory
Molecular dynamics
Monte Carlo simulation
Phase-field modeling
High-performance computing
Scientific Python
AI/ML techniques
Active learning
Bayesian optimization
Reinforcement learning
Autonomous lab systems

Additional Information

Minimum Education: PhD in materials science, chemistry, physics, chemical engineering, mechanical engineering, biophysics, or a closely related field
Required Previous Experiences: Experience in atomistic simulation and computational materials science, including density functional theory, molecular dynamics, Monte Carlo simulation, phase-field modeling, multiscale modeling, or high-performance computing
Programming and software engineering experience with the scientific Python ecosystem or equivalent computational tools
Experience applying AI or machine learning techniques to scientific problems, including active learning, Bayesian optimization, reinforcement learning, automated workflows, or autonomous lab systems
Experience conducting independent research, including research question formulation, complex data analysis, and prototype or proof-of-concept development
Research impact through peer-reviewed publications, patents, open-source software contributions, or equivalent professional accomplishments
Preferred Qualifications: Experience validating atomistic simulation results against experimental data and collaborating with experimental teams
Broad scientific network for collaboration with researchers and institutions
Experience with industry-academic partnerships or multidisciplinary research consortia