Physics Research Internship
About the Office:
The research internship is hosted in the Department of Physics & Astronomy at the University of Tennessee, Knoxville, within a computational biophysics group.
About the VOLinternship Program:
The VOLintern Program is UTK's on-campus internship program. Each internship will run for the duration of one academic semester. Students will be able to gain real work experience without leaving campus! Gain access to real-world experience, enhanced professional development, and industry mentors by applying now!
About the Internship:
We are seeking a motivated undergraduate researcher to join our group in Spring (10 weeks, ~8 hours/week), with the possibility of renewal for an additional 10-week appointment in the summer. The project focuses on developing and applying machine-learning-assisted approaches to study Group VI oxyhalide van der Waals ferroelectric materials. The intern will work in a Linux-based computing environment and contribute to algorithm development, data processing, and simulation workflows. This position offers hands-on experience with state-of-the-art computational materials research and opportunities for extended involvement in ongoing projects.
Internship Responsibilities:
- Assist in building machine-learning models to analyze structural and ferroelectric properties of oxyhalide materials
- Prepare, run, and monitor simulations using Python in Linux/HPC environments
- Contribute to DFT, MD, or related computational workflows (training will be provided if needed)
- Perform data cleaning, visualization, and quantitative analysis of simulation outputs
- Participate in weekly research meetings and maintain organized documentation of results
- Collaborate with graduate students and the PI on research milestones and deliverables
Qualifications
- Major in Physics, Materials Science, Engineering, or a closely related STEM field
- Strong motivation and ability to work independently
- Experience with Python programming and familiarity with a Linux environment
- Interest in machine learning or computational materials research
- Preferred (but not required): prior exposure to machine learning frameworks, DFT, MD simulations, or high-performance computing
- Good communication skills and willingness to learn new computational tools
How to Apply:
- Apply via Handshake by submitting your Resume and Cover Letter
- For preference, please make sure to address how this position with help you gain experience for your career goals and how an on-campus internship with benefit you in your Cover Letter.