Training

An immersive dive into machine learning best practices and applications in life sciences. This week-long in-person workshop guides participants through machine learning fundamentals up to cutting edge deep learning tools and methodologies for implementation in life sciences research. Attendees will also gain hands-on experience utilizing data from the National Institutes of Health's Common Fund Data Ecosystem, learn effective techniques to prepare and manage preprocessing of datasets, and learn how to train and deploy their own models efficiently and accurately.

An immersive dive into machine learning best practices and applications in life sciences. This week-long in-person workshop guides participants through machine learning fundamentals up to cutting edge deep learning tools and methodologies for implementation in life sciences research. Attendees will also gain hands-on experience utilizing data from the National Institutes of Health's Common Fund Data Ecosystem, learn effective techniques to prepare and manage preprocessing of datasets, and learn how to train and deploy their own models efficiently and accurately.

An immersive dive into machine learning best practices and applications in life sciences. This week-long in-person workshop guides participants through machine learning fundamentals up to cutting edge deep learning tools and methodologies for implementation in life sciences research. Attendees will also gain hands-on experience utilizing data from the National Institutes of Health's Common Fund Data Ecosystem, learn effective techniques to prepare and manage preprocessing of datasets, and learn how to train and deploy their own models efficiently and accurately.

An immersive dive into machine learning best practices and applications in life sciences. This week-long in-person workshop guides participants through machine learning fundamentals up to cutting edge deep learning tools and methodologies for implementation in life sciences research. Attendees will also gain hands-on experience utilizing data from the National Institutes of Health's Common Fund Data Ecosystem, learn effective techniques to prepare and manage preprocessing of datasets, and learn how to train and deploy their own models efficiently and accurately.

An immersive dive into machine learning best practices and applications in life sciences. This week-long in-person workshop guides participants through machine learning fundamentals up to cutting edge deep learning tools and methodologies for implementation in life sciences research. Attendees will also gain hands-on experience utilizing data from the National Institutes of Health's Common Fund Data Ecosystem, learn effective techniques to prepare and manage preprocessing of datasets, and learn how to train and deploy their own models efficiently and accurately.

Spend a week with TACC HPC experts learning how to effectively use supercomputing for research and code development. The course introduces core parallel programming paradigms used in HPC, including CUDA, MPI, OpenMP, and OpenMP offloading, along with essential HPC tools. Participants complete hands-on labs using TACC systems and can attend additional sessions on Julia, modern C++, and the CMake ecosystem for scientific software development.

The OSPOSIUM will bring together a broad set of scientists, engineers, students, and researchers from across the UT system who use, or are interested in using, open source software to advance their research. This meeting will feature a series of talks and panels highlighting efforts to date and featuring opportunities to collaborate. The event will consist of a full day of presentations with a reception on Wednesday, September 23, followed by a student-focused event, “Open to Work” on Thursday, September 24. This meeting will immediately follow TACCSTER 2026, the two-day annual symposium for Texas-based users of the Texas Advanced Computing Center (TACC).

The OSPOSIUM will bring together a broad set of scientists, engineers, students, and researchers from across the UT system who use, or are interested in using, open source software to advance their research. This meeting will feature a series of talks and panels highlighting efforts to date and featuring opportunities to collaborate. The event will consist of a full day of presentations with a reception on Wednesday, September 23, followed by a student-focused event, “Open to Work” on Thursday, September 24. This meeting will immediately follow TACCSTER 2026, the two-day annual symposium for Texas-based users of the Texas Advanced Computing Center (TACC). To broaden participation in the OSPOSIUM from across the University of Texas System, we are supporting up to ten Travel and Participation Stipends for students. The stipends are intended to cover registration, travel, and accommodation expenses incurred for attending the OSPOSIUM in Austin. Applications are due by July 6, 2026.