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Computational Materials Scientist
2 months ago
Bosch Research is seeking highly motivated interns to join our materials design team, specializing in atomistic computational materials science.
About the RoleWe are committed to improving Bosch products through a deep understanding of thermodynamic, kinetic, and transport phenomena on an atomic level using both quantum and classical simulations.
Our goal is to develop and apply computational and machine-learning methods for understanding and automated discovery of next-generation materials, including for electrochemistry, energy conversion, sensors, and sustainability.
Responsibilities- Development and application of atomistic methods for understanding thermodynamics, kinetics, and transport
- Computational discovery of next-generation materials systems for technology applications
- Designing and implementing code for high-performance and high-throughput computing, including machine-learning methods
We are looking for Ph.D. candidates at top universities in chemical engineering, physics, chemistry, materials science, or a related field.
Experience in atomistic simulations, including at least one of: density-functional theory, molecular dynamics, and quantum chemistry is required.
Solid foundations in materials science, solid-state physics, and/or chemistry are essential.
Desired QualificationsSignificant research experience, including high-impact publications, patents, and/or open-source codes is highly desirable.
Strong background in physics and coding, and passion for working and understanding physics-based devices is a plus.
Atomistic simulation experience including one or more of: machine-learned interatomic potentials, data-driven material design, large biomolecules, reaction kinetics, polymer physics, PEM fuel cells, or tribology is highly valued.
Experience applying machine learning or artificial intelligence to atomistic physics simulations is a strong asset.
What We OfferThe U.S. base salary range for this intern position is $30.00-$58.00 per hour.
Individual pay is determined based on several factors, including, but not limited to, type of degree, work experience and job knowledge, complexity of the role, type of position, job location, etc.
We are committed to a diverse workforce and are an equal opportunity employer.
We are a proud supporter of STEM education and initiatives.