INTERNSHIP DETAILS

MLIPs Multi-Fidelity Intern

CompanyBosch Group
LocationWatertown
Work ModeOn Site
PostedMay 18, 2026
Internship Information
Core Responsibilities
The intern will develop and apply multi-fidelity Machine Learning Interatomic Potential (MLIP) frameworks and workflows. Responsibilities include creating best practice guidelines and implementing code for high-performance and high-throughput computing.
Internship Type
intern
Salary Range
$30 - $59
Company Size
160203
Visa Sponsorship
No
Language
English
Working Hours
40 hours
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About The Company
The Bosch Group is a leading global supplier of technology and services. It employs roughly 413,000 associates worldwide (as of December 31, 2025). The company generated sales of 91 billion euros in 2025. Its operations are divided into four business sectors: Mobility, Industrial Technology, Consumer Goods, and Energy and Building Technology. With its business activities, the company aims to use technology to help shape universal trends such as automation, electrification, digitalization, connectivity, and an orientation to sustainability. In this context, Bosch’s broad diversification across regions and industries strengthens its innovativeness and robustness. Bosch uses its proven expertise in sensor technology, software, and services to offer customers cross-domain solutions from a single source. It also applies its expertise in connectivity and artificial intelligence in order to develop and manufacture user-friendly, sustainable products. With technology that is “Invented for life,” Bosch wants to help improve quality of life and conserve natural resources. The Bosch Group comprises Robert Bosch GmbH and its roughly 500 subsidiary and regional companies in over 60 countries. Including sales and service partners, Bosch’s global manufacturing, engineering, and sales network covers nearly every country in the world. Bosch’s innovative strength is key to the company’s further development. At 136 locations across the globe, Bosch employs some 82,000 associates in research and development. Instagram: https://www.instagram.com/boschglobal/ Facebook: https://www.facebook.com/BoschGlobal Glassdoor: https://bit.ly/3raTZnH Imprint: www.bosch.com/corporate-information Privacy statement: https://www.bosch.com/data-protection-notice-bosch-linkedin/
About the Role

Company Description

The Bosch Research and Technology Center North America with offices in Sunnyvale, California, Pittsburgh, Pennsylvania and Watertown, Massachusetts is part of the global Bosch Group (www.bosch.com), a company with over 90 billion euro revenue, 400,000 people worldwide, a very diverse product portfolio, and a history of over 125 years. The Research and Technology Center North America (RTC-NA) is committed to providing technologies and system solutions for various Bosch business fields primarily in the areas of Human Machine Interaction (HMI), Robotics, Energy Technologies, Internet Technologies, Circuit Design, Semiconductors and Wireless, and MEMS Advanced Design.

The Computational Materials Science team in Watertown specializes in atomistic and mesoscale simulation to improve Bosch products through deep understanding of thermodynamic, kinetic, and transport phenomena on an atomic level. Using quantum mechanical and classical simulations, and machine learning, our team focuses on application areas which include electrochemistry, energy conversion, sensors, and sustainability. Our work directly contributes to the development of innovative solutions for real-world challenges.

Job Description

We are seeking a highly motivated and skilled intern for a 1.5 year (until Dec 2027) internship in our Computational Materials Science team. The intern will focus on MLIP multi-fidelity frameworks, workflows, review literature, and prepare presentations of results for project team meetings.

 

Key responsibilities:

  • Development and application of multi-fidelity MLIP frameworks and workflows
  • Develop best practice guidelines for multi-fidelity MLIPs setup and inference
  • Designing and implementing code for high-performance and high-throughput computing

Learning and development opportunities

Interns gain hands-on experience in industry research alongside experienced engineers and fellow interns. Past interns often complete one or more patents, software packages, or publications, as well as develop valuable skills in their careers. Approximately half of associates on our team are former interns, demonstrating a potential for long-term growth and opportunities.

Qualifications

Candidates must have:

  • Current PhD candidate at a top university in chemical engineering, physics, chemistry, materials science, or a related field
  • Minimum GPA of 3.0
  • Experience in running atomistic-scale simulations via MLIPs as well as electron-based methods to train MLIPs
  • Solid foundations in materials science, solid-state physics, and/or chemistry
  • Attention to detail, flexibility, creativity, and excellent communication and teamwork skills
  • A cover letter describing why the candidate is suited for the position

Desired qualifications:

  • Significant research experience, including high-impact publications, patents, and/or contributions to open-source codes
  • Strong background in physics and coding, and passion on working and understanding physics- and chemistry-based devices
  • Proven ability to design research objectives, conduct independent research, and develop expertise in a specific field.

Additional Information

The U.S. base salary range for this intern position is $30.00-$59.00 per hour. Within the range, 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. Your Hiring Manager can share more details about the specific salary range for this position during the interview process.*

All your information will be kept confidential according to EEO guidelines.

  • Legal Entity: Robert Bosch LLC
  • Key Skills
    Multi-fidelity MLIP FrameworksAtomistic-scale SimulationsElectron-based MethodsHigh-performance ComputingHigh-throughput ComputingMaterials ScienceSolid-state PhysicsChemistryChemical EngineeringCodingResearch DesignTechnical Communication
    Categories
    Science & ResearchEngineeringTechnologyData & AnalyticsEnergy