The Texas Advanced Computing Center (TACC) at The University of Texas at Austin is one of the leading supercomputing centers in the world, supporting advances in computational research by thousands of researchers and students. TACC staff help researchers and educators use advanced computing, visualization, and storage technologies effectively, and conduct research and development to make these technologies more powerful, more reliable, and easier to use. TACC staff also educate and train the next generation of researchers, empowering them to make discoveries that advance knowledge and change the world.
The Texas Advanced Computing Center fosters a culture of innovation, passion, and fun by encouraging staff members to actively collaborate to investigate the latest technologies, team up for charities, and celebrate successes together. TACC promotes a healthy workplace by helping employees achieve balance between their personal and professional lives to increase employee engagement, job satisfaction, and overall well-being.
Candidates will need to upload a resume, letter of interest, unofficial copy of transcript and the names of three references to apply for this position.
UT Austin offers a competitive benefits package that includes:
- 100% employer-paid basic medical coverage
- Retirement contributions
- Paid vacation and sick time
- Paid holidays
Please visit our Human Resources (HR) website to learn more about the total benefits offered.
If you are not sure that you’re 100% qualified, but up for the challenge – we want you to apply. We believe skills are transferable and passion for our mission goes a long way.
Purpose
Position will provide leadership and technical expertise to TACC’s HPC research, development, and support initiatives. Expertise in one of the following or related technical domains is essential for this role: optimization of applications for multi-accelerator nodes, optimization of algorithms for accelerators, implementation of machine learning frameworks.
Responsibilities
- Work with TACC users to integrate HPC technologies into their research and development activities and to measure the impact of TACC’s HPC systems on their research capabilities.
- Perform application performance analysis and industry standard benchmarking on HPC platforms.
- Evaluate new HPC architectures, systems, and software tools to determine best practices and identify future acquisition targets.
- Assist TACC users with the porting, analysis, and improvement of their research software on TACC’s HPC systems.
- Initiate and conduct research into new high performance and parallel computing applications, techniques, tools, and algorithms.
- Publicize the results of these activities through presentations at conferences/workshops and through publications in proceedings and professional journals.
- Pursue and obtain external funding to enhance TACC’s HPC activities, expertise, and resources by submitting proposals to funding agencies, industrial partners, and vendors directly or in partnership with researchers and faculty at UT Austin or other institutions.
Required Qualifications
- Doctoral degree in a discipline relevant to this position.
- Research experience using high performance computing including at least two relevant publications.
- Proficiency with common HPC programming languages, tools, and technologies: e.g. C/C++, CUDA, Fortran, MPI, OpenMP.
- Experience in developing parallel applications.
- Demonstrated expertise working in collaborative, interdisciplinary projects with computational scientists and engineers.
- Excellent interpersonal communication skills and professional demeanor.
Preferred Qualifications
- Experience debugging and profiling molecular dynamics applications that use accelerators.
- Experience optimizing algorithms for accelerators using CUDA.
- Experience programming for Grace Hopper architectures.
- Interest in teaching or producing HPC training materials related to accelerator programming.
Salary Range
$90,000 + depending on qualification
Working Conditions
- Typical office environment
Required Materials
- Resume/CV including a list of publications
- 3 work references with their contact information; at least one reference should be from a supervisor
- Letter of interest
- Unofficial copy of transcript
