The Research Experiences in Computational Science, Engineering, and Mathematics (RECSEM) REU site program begins in 2017. This site program at the University of Tennessee (UTK) directs a group of ten undergraduate students to explore the emergent interdisciplinary computational science models and techniques via a number of cohesive compute and data intensive applications. The RECSEM program complements the growing importance of computational sciences in many advanced degree programs and provides scientific understanding and discovery to undergraduates with an intellectual focus on research projects on high performance computing (HPC) platforms. This program aims to deliver a real-world research experience to the students by partnering with teams of scientists who are in the forefront of scientific computing research at the National Institutes of Computational Sciences (NICS), the Innovative Computing Laboratory (ICL), and the Joint Institute for Computational Sciences (JICS) at UTK and Oak Ridge National Laboratory. After the summer program, the REU participants may choose to continue their research efforts at their home institutions. Ten additional international students supported by our partner universities in Hong Kong also participate in this program. Together the students of RECSEM work collaboratively to achieve their research tasks, and at the same time share a unique opportunity for trading academic experiences, scientific ideas, and cultural social activities in this ten week long program.
This program is organized around a synergistic theme of ideas and practices those are common to many scientific applications. The research projects are categorized in three interrelated areas of research interests: engineering applications, numerical mathematics, and linear algebraic software and tools. The scope of work for these projects put emphasis on conducting software development, model implementation, and design and evaluation of numerical experiments under the guidance of a team of experts in each scientific domain. Projects include computation in multi-scale materials science and bio-mechanics applications, simulation of traffic flow phenomena, implementation of high order parallel numerical schemes, and processing of images with different techniques and algorithms of machine learning and data analytics. The students have opportunities to perform large-scale scientific simulations on HPC clusters as well as world-class state-of-the-art supercomputers equipped with the latest hardware technologies provided by the Extreme Science and Engineering Discovery Environment (XSEDE) organization. These latest computing units include graphical processing units (GPUs) and multicore processors. This program is organized in four major stages: HPC training, research formulation, project action, and scientific reporting. These stages aim to gradually assist the students towards finishing their research projects in time with appropriate level of motivation and guidance.
The application requirements are:
- Two letters of recommendation from professors on school letterhead *
- Official Transcripts from all universities and colleges you have attended *
- Goal statement
* Letters of recommendation and transcripts can be sent either electronically (scanned and emailed) or by regular mail. For scanned copies you will still be required to provide the original documents upon request.
The 2023 RECSEM program runs tentatively from May 30 till August 5. The program is limited to U.S. Citizens or permanent residents.
Application deadline is February 20, 2023. Should you have any questions, please don't hesitate to contact us via email: firstname.lastname@example.org.
Each student accepted by the program receives a stipend of $600 per week. In addition, students may receive $220/per week for housing/subsistence, if necessary, a travel stipend of up to $800.
Send e-mail to:
Dr. Kwai Wong
Joint Institute for Computational Sciences
University of Tennessee
Claxton Bldg., room 330
1122 Volunteer Blvd.
Knoxville, TN, 37996-3460
Email : email@example.com