Visiting Student-TPS- Adwoa, Adunyah- 8.11.26

Argonne National Laboratory • Lemont, IL

11d • Onsite

About The Position

This internship, supported by NSF funding, offers an opportunity to gain hands-on experience in machine learning applied to fuel cell break-in and conditioning. The student will receive mentorship in developing and applying ML models to optimize conditioning parameters, with the goal of reducing the overall break-in and conditioning time. Through this project, the intern will acquire practical skills in data analysis, modeling, and experimental optimization within a collaborative research environment. Xiaohua Wang and Dionissios Papadias from Argonne will serve as mentors to the student. It is confirmed that neither Dr. Hall nor the graduate student have a financial interest in Argonne.

Requirements

• Must be 18 years or older at the time the appointment begins.
• Currently enrolled in undergraduate or graduate studies at an accredited institution.
• Graduated from an accredited institution within the past 3 months.
• Actively enrolled in a graduate program at an accredited institution.
• The entirety of the appointment must be conducted within the United States.

Responsibilities

• Develop and apply ML models to optimize fuel cell break-in and conditioning parameters.
• Reduce overall break-in and conditioning time.
• Acquire practical skills in data analysis, modeling, and experimental optimization.
• Work within a collaborative research environment.

What This Job Offers

• Job Type: Part-time
• Career Level: Entry Level
• Education Level: Associate degree