Program Contact
For questions regarding this program, please contact: kelly.tagle@oden.utexas.edu
Interested in learning more about our interns' Moncrief experience? Check out these articles:
Moncrief Internship Helps Student's Quest to Solve Inverse Problems
Building Skills, Connections, and Confidence: 2025 Moncrief Summer Internship Program
Crossing Disciplines: Insights from the Moncrief Interns of 2024
Unlocking Potential: Insights from the Moncrief Interns of 2023
Moncrief Summer Internship
Deadline: February 1, 2026
The Moncrief Undergraduate Summer Internship Program provides summer support for qualified undergraduate students of mathematics, science, and engineering to work within the Oden Institute for Computational Engineering and Sciences during the summer months.
Interns work with faculty and research staff from one of the Oden Institute's research centers and groups on one of a wide range of research topics. Research activities generally focus on developing modeling and simulation methods to study problems in areas such as energy, environment, advanced materials, biomedical research, nanomanufacturing, autonomous systems, and many other scientific and engineering areas that draw on applied and computational mathematics, computing, fluid mechanics, solid mechanics, mathematical physics, and biology.
Eligibility Requirements
For participation in the Summer 2026 program applicants must be U.S. citizens or permanent residents* who are currently enrolled in an undergraduate institution and will be entering their junior or senior year in Fall 2026.
*International students may apply if they are currently enrolled at the University of Texas at Austin.
Internship Information
- Dates: June 1 – August 7, 2026
- Support: The internship will provide a $6,500 stipend paid directly to the student, plus housing in a UT Austin dorm, a meal plan, and some funding to defray travel costs to/from Austin. UT Austin students with existing housing may elect for a housing stipend in lieu of on campus housing and dining.
- Project assignment: Interns will be assigned a faculty supervisor in one of the Oden Institute's Research Centers or Groups and will work with faculty, graduate students, and postdocs.
Application Deadline: February 1, 2026
Applicants will be notified of decisions by March 6, 2026.
How to Apply
Submit the Online Application and upload the following materials:
- Resume
- Personal Statement — Write a 1-page (double-spaced) statement describing why you wish to participate in the Moncrief Summer Internship Program. State your post-graduation career goals. You may include your past and current research experience if applicable.
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Official transcript(s).
- Non UT Austin students: PLEASE NOTE — this is a COPY of your official transcript (i.e. get your official transcript, scan it, and then upload it). Copies of unofficial transcripts (such as those printed from your university's website) will not be accepted.
- UT AUSTIN STUDENTS: Do not upload your transcript. Provide your UT EID on the application form and we will access your transcript.
Two (2) letters of recommendation are required. Please provide the Name, Institution, and Email Address of your references on the Application and we will contact your references directly.
Please label all files in the following format: Last Name, First Name_File Type (i.e., Resume, Personal Statement, Transcript).
Previous summer research topics
Comparing Activation Functions to Corresponding B-functions
Supervisor: Tan Bui-Thanh
Machine Learning for Molecular Dynamics
Supervisor: Don Siegel
Autonomy Simulations in STK and Onesky
Supervisor: Ufuk Topcu
Analysis of Model Prediction for Behavior Based on Neural Activities with t-SNE Visualization of Network Embeddings
Supervisor: Atlas Wang
Efficient High-Speed Neural Network Models for Biological Materials
Supervisor: Michael S. Sacks
Determination of fall-risk in transitional movements using markerless motion capture techniques
Supervisor: Joshua Chang
Implementing and Benchmarking Learning Algorithms for Neural Network Potentials
Supervisor: Graeme Henkelman
A framework for stochastic, size-structured neutral model for community
Supervisor: Annette Ostling
NODE-FNO and C-FNO: Improve Fourier Neural Operators through Adjoint Training and Conservation Enforcing
Supervisor: Chandrajit Bajaj
Employing magnetic resonance imaging data to implement a mathematical model of glioblastoma progression
Supervisor: Tom Yankeelov
Modeling Single File Dynamics using the Generalized Langevin Equation
Supervisor: Dmitrii E. Makarov