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Alston S. Householder


The Computer Science and Mathematics (CSM) Division at the Oak Ridge National Laboratory (ORNL) invites outstanding candidates to apply for the Alston S. Householder Fellowship in mathematics and scientific computing. This prestigious Fellowship offers an excellent opportunity to conduct exceptional and innovative research in mathematics, statistics and scientific computing, for applications of national priority, utilizing the world's most powerful extreme scale computing platforms, including TITAN.

The Fellowship honors Dr. Alston S. Householder, founding director of the Mathematics Division (now CSM Division) at ORNL and recognizes his seminal research contributions to the fields of numerical analysis and scientific computing. Funding for the Householder Fellowship comes from the Computational & Applied Mathematics Group (CAM), which is supported by the Office of Advanced Scientific Computing Research (ASCR) of the U.S. Department of Energy.  Additional information about the CAM at ORNL can be found at


Each Householder Fellowship appointment is for one year with the option to renew for a second year or third year. The fellowship offers collaborative research opportunities in active programs at ORNL, a highly competitive salary, moving expenses, and a generous professional travel allowance. The selected individual will be mentored by a senior scientist within the CAM, but are encouraged to pursue their own research agenda, through access to the most advanced computer architectures, and opportunities to facilitate technology transfer from the laboratory research environment to industry and academia through training of new computational scientists.

ORNL’s applied mathematics research efforts provide the fundamental mathematical methods and algorithms needed to model complex physical, chemical, and biological systems. ORNL’s computational science research efforts enable scientists to efficiently implement these models at the extreme-scale of computing, and to store, manage, analyze, and visualize the massive amounts of data that result. Finally, ORNL’s statistics research provides the techniques to link the data producers, e.g., supercomputers and large experimental facilities, with the data consumers, i.e., scientists who need the data.

Qualifications Required

  • The minimum required education is a Ph.D. in applied mathematics, statistics or computational science, but no more than four years beyond completion can be considered.  
  •  A proven academic record of high quality research with clear potential to perform cutting edge, innovative research in applied mathematics, statistics and/or computational science.
  • The successful candidate will have a strong background and expertise in more than one area of particular relevance to the CAM at ORNL. 
  • Principal research areas include:
    • Multi-scale methods, including atomistic-to-continuum coupling;
    • Computational kinetic theory;
    • Computational fluid dynamics and turbulence;
    • High-dimensional approximation theory;
    • Large-scale iterative methods for linear and eigenvalue problems;
    • Numerical methods for stochastic (partial) differential equations;
    • Uncertainty quantification;
    • Probability theory
    • Statistical sampling and design of experiments;
    • Combinatorial optimization and graph theory;
    • Computational geometry and mesh generation
    • Sparse methods for data analytics
    • High-order continuous and discontinuous methods for PDEs
    • Multi-resolution analysis

U.S. citizenship and a security clearance are NOT required for this position.


For more information about the Householder Fellowship or for technical questions please contact Clayton Webster (


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