VIPR-GS Internship

Research Efforts

Primarily an engineering research effort, VIPR-GS has over 35 active research efforts with over 80 involved faculty members from the following departments:

We are seeking student interns eager to support research across these disciplines; however, some targeted opportunities are described below. Please note that applications will be accepted for all disciplines mentioned above, even if they are not included in the target list below. Applicants whose backgrounds and interests align with our research will be invited to interview with a faculty member. Highly ranked candidates will be offered the opportunity to conduct a research internship throughout the next academic year.

Interns will be expected to work 10 hours per week, collaborating with VIPR faculty and contributing to research efforts. Please note that weekly hours may vary depending on the student's schedule and research requirements. Compensation is set at $12.50 per hour. The VIPR-GS Research Center may also request interns' availability for feature spotlights, videos, and testimonials.

Current targeted opportunities:

• Computer Science, Mechanical Engineering, Electrical and Computer Engineering
  • The objective of the project is to develop data-driven methods for the control of off-road vehicles. The application of the developed methods will be demonstrated on a real hardware platform.
  • Relevant coursework includes control systems, optimization, signal processing, and computing.
  • Specialized skills include experience coding in MATLAB or Python.
  • Physical work location: in-person on main campus and occasional ‘field’ locations.
• Mechanical Engineering, Electrical and Computer Engineering
  • This project will focus on the thermal and electrical modeling of battery modules and the integration with the vehicle. The detailed tasks include the implementation of battery state estimation algorithms, the communication with the battery disconnection unit and the electric control units, and the testing of the designed system.
  • Relevant coursework includes Junior or Major in electrical or mechanical engineering
  • Specialized skills and experience include: Battery experience is a great plus.
  • Physical work location: CU-ICAR campus
• Mechanical Engineering, Electrical and Computer Engineering, Automotive Engineering, School of Computing
  • The project develops and tests AI-based algorithms for managing battery packs (charging, balancing, diagnostics, thermal management). This involves hybrid model learning combining physics with real-time data, and learning optimal and adaptive management actions using various deep learning architectures.
  • Relevant coursework includes systems dynamics, machine learning, and control systems.
  • Specialized skills and experience include: familiarity with machine learning algorithms involving neural networks or willingness to learn quickly, and hands-on experience building test circuits (with batteries or other items), working with electrical hardware/test systems.
  • Physical work location: Both in-person at CU-ICAR and remote (virtual) work is available.
• Physics, Mechanical Engineering, Materials Science and Engineering
  • In this project, we are experimentally preparing BN-based thermal interface materials and evaluating them at different temperatures and charging rates. Our goal is to optimize the composite to achieve cross-plane conductivity of >15 W/mK, which is considered to be challenging. We are also employing novel machine learning methods to estimate thermal interfacial resistance.
  • Relevant coursework includes solid-state physics, Heat transfer, and Fluid dynamics.
  • Specialized skills and experience include: experience with battery modeling or machine learning is useful, but not necessary.
  • Physical work location: G09 Kinard Lab of Physics on Clemson Main campus.
• Physics, Chemistry, Chemical Engineering, Materials Science and Engineering
  • This project uses physics-based electrolyte models to uncover structure-property relationships to achieve a stable solid-electrolyte interface, low desolvation energy, and a high transference number. Silicon nanoquils – a novel form of nano-silicon – will be used as the anode active materials, which the intern will be trained to synthesize during their internship.
  • Specialized skills and experience include: Students with a strong chemistry or chemical engineering background are preferred, although we can train students with another scientific background. No prior lab experience is required.
  • Physical work location: Clemson Nanomaterials Institute, located at AMRL.
• Computer Science, Mechanical Engineering, Electrical and Computer Engineering
  • Support for this opportunity requires Knowledge of Robot Operating System (ROS) and related sensors.
  • This effort supports work on a full-scale off-road autonomous vehicle (POLARIS RZR) for data collection and autonomy testing.
  • Both in-person (at CU-ICAR) and remote work are available.