Postdoctoral Research Associate - Sparse Algorithms

Oak Ridge National Laboratory • Oak Ridge, TN

4d • Onsite

About The Position

The Discrete Algorithms Group at Oak Ridge National Laboratory (ORNL) seeks a postdoctoral researcher for a two-year position specializing in sparse algorithms. This researcher will focus on advancing secure, trustworthy, and efficient AI solutions for scientific applications by developing state-of-the-art sparse algorithms in matrices, tensors, and networks. These algorithms will support large-scale numerical, scientific, and AI models. The researcher will also disseminate findings through publications and presentations in top-tier peer-reviewed journals and conferences. To conduct this work, the successful candidate will use the world's first exascale system, Frontier, and collaborate with leading experts in machine learning, optimization, electric grid analytics, and scientific imaging.
The primary responsibility of this position is designing and implementing sparse algorithms for large-scale scientific and numerical computations. The successful candidate will pursue an ambitious research agenda to drastically advance the state of the art in sparse computation. This research will explore sparse computations both as a unified topic and within three broad pillars: sparse and structured matrix computations, sparse tensor problems, and sparse network problems, as well as their interconnections. These efforts will yield significant theoretical and applied contributions, helping to advance sparse AI and numerical systems globally.

Requirements

• A PhD in Computer Science, Applied Mathematics, Computational Science, or a related discipline.
• Demonstrated depth in at least one of the areas of specialization listed below, evidenced by publications, software, or comparable research output.
• Demonstrated hands-on experience developing and applying HPC algorithms to sparse numerical, scientific, and ML models.
• Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment.

Nice To Haves

• Strong expertise in two or more of the following areas is preferred, and an exceptionally strong candidate in a single area is also encouraged to apply. Relevant areas include: Parallel and distributed graph and or ML algorithms — shortest paths, connectivity, clustering, or graph traversal on GPU clusters and distributed-memory systems.
• Sparse direct and iterative linear solvers — communication-avoiding methods, sparse LU factorization, sparse triangular solves, or preconditioning.
• Mixed-precision and approximate numerical computation — floating-point error analysis, iterative refinement, or exploiting low-precision arithmetic on modern accelerators.
• Sparse and constrained tensor decompositions — CP- or Tucker-type factorizations, constrained least-squares solvers, or scalable tensor kernels.
• GPU performance engineering — CUDA/HIP kernel design, communication–computation trade-offs, or performance modeling on heterogeneous systems.
• Theory of parallel algorithms — communication lower bounds or work–depth analysis of sparse and graph computations.

Responsibilities

• Designing novel sparse algorithms — including mixed-precision, energy-efficient, and accelerator-optimized methods — for large-scale numerical, scientific, and/or AI models.
• Demonstrating the scalability of new algorithms on leadership supercomputers for large-scale problems of national and societal interest.
• Developing mathematical analyses to bound the trade-offs between performance, energy efficiency, and time, especially in the context of sparse computations.
• Communicating research via publications and conference presentations in top venues, invited talks, and organized workshops, tutorials, and symposiums.
• Releasing research software as open-source libraries and contributing to community codes.
• Collaborating with domain scientists to apply sparse algorithms to DOE mission applications and mentoring and working with undergraduate and graduate students.

Benefits

• medical and retirement plans
• flexible work hours
• Prescription Drug Plan
• Dental Plan
• Vision Plan
• 401(k) Retirement Plan
• Contributory Pension Plan
• Life Insurance
• Disability Benefits
• Generous Vacation and Holidays
• Parental Leave
• Legal Insurance with Identity Theft Protection
• Employee Assistance Plan
• Flexible Spending Accounts
• Health Savings Accounts
• Wellness Programs
• Educational Assistance
• Relocation Assistance
• Employee Discounts

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree