Computational Materials Science Intern

We are seeking highly motivated and skilled interns for a 3-6 month internship in our Computational Materials Science team. The intern will focus on one or more of the following areas and will be expected to write reports, review literature, and prepare presentations of results for project team meetings.

Key responsibilities:

• Development and application of atomistic and/or mesoscale methods for understanding thermodynamics, kinetics, degradation, and transport phenomena
• Computational discovery and/or characterization of next-generation materials systems
• Designing and implementing code for high-performance and high-throughput computing, including machine-learning methods

Anticipated 2025 projects: Candidates are strongly encouraged to highlight relevant atomistic experience and projects of interest in their cover letters/resumes.

1. Salt hygroscopy in the context of electrolyte behavior and environmental corrosion
2. System and materials design for carbon capture
3. Polymer degradation through radical attack and temperature swings
4. Soft matter (atomistic and/or mesoscale) mechano-chemical properties (from adhesion to quasi-static and frequency-dependent responses).
5. Nanofluidic channel design and modeling, especially coupled with electromagnetic fields
6. Tribology and lubricant modeling and selection, including mechanochemical degradation and additives considerations.
7. Degradation and ion migration induced by adsorbed water layers in microelectronics
8. Abrasion, wear, and degradation in high-voltage microelectronic contacts Multiphase modeling including microscopic phase-field models coupled to atomistic simulations

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.

Required Qualification:

Candidates must have

• Current PhD candidate at a top university in chemical engineering, physics, chemistry, materials science, or a related field
• Experience in running or interacting with atomistic-scale simulations, including at least one of: density-functional theory, molecular dynamics, quantum chemistry or phase-field
• 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, past computational materials science experiences, and the desired project choice(s)

Desired Qualification:

• 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
• Past experience directly comparing experimental measurements with computational materials science simulations
• Proven ability to design research objectives, conduct independent research, and develop expertise in a specific field
• Past experience relevant to one or more of the projects listed