The Texas Advanced Computing Center (TACC) is looking to solve challenging problems in science and engineering by developing and applying AI/ML techniques to accelerate scientific discovery and innovation in various domain areas.
Requirements
- Hands-on experience with AI/ML techniques and platforms.
- Experience with large language models (LLMs), multimodal ML, and/or agentic AI to automate, optimize, and advance scientific and engineering research workflows.
- Experience in developing or applying surrogate modeling to accelerate simulations or approximate complex physical processes.
- Experience with supporting and extending open-source and open-data products for research communities
- Experience analyzing both measured and simulated data sources.
- Experience training and mentoring researchers in data workflows and best practices for incorporating AI/ML methods.
- Strong problem-solving and strategic-thinking skills, with the ability to translate emerging AI technologies into practical solutions for science and engineering.
Responsibilities
- Consult and collaborate with data providers, analysts, systems experts, and research staff to design, develop, and deploy advanced AI/ML systems for defined project requirements.
- Mentor TACC staff in machine learning, data analytics, and emerging methods (e.g., prompt engineering, workflow orchestration with AI agents, deployment on HPC systems, etc.).
- Support the application of AI/ML across a diverse range of scientific domains.
- Support training of AI/ML techniques and best practices to a broad range of researchers
- Collaborate and propose new funding opportunities supporting research done at TACC.
- Prepare reviewed papers, technical reports, design, and requirements of data analytic techniques and systems, optimizations, and novel applications across domains supported at TACC.
- Stay at the forefront of new techniques and technologies applicable to AI/ML systems that support implementations in various science and engineering domains.
Other
- Ph.D. in science, engineering, computer science, or related research field with a strong background in applied AI/ML and data analytics.
- Excellent written and verbal communication skills.
- Ability to quickly learn and adapt new technologies—especially emerging AI tools, platforms, and frameworks.
- Relevant education and experience may be substituted as appropriate.
- 3 work references with their contact information; at least one reference should be from a supervisor
