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Alston S. Householder


The Computational & Applied Mathematics (CAM) Group, within 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 and SUMMIT. ORNL’s CAM 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. Additional information about CAM at ORNL can be found at 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.


Applications for the Householder Fellowship will be solicited once each year, during the period of September 1 - November 31 on the ORNL Career’s Website.

Each Householder Fellowship appointment is fully funded for a period of three years for recipients with proven exceptional academic records and achievements, along with formal mentorship and guidance designed to facilitate successful integration and alignment of their research activities within DOE programs. Recipients are expected to conduct research of the highest quality and impact, elevate the reputation of the Laboratory, and become scientific leaders in their field. 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 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 Mathematicians and computational scientists.

Qualifications Required

  • Each applicant must be the recipient of an earned doctorate in Applied Mathematics, Statistics, Computational Science or related field and, with rare exceptions, must be no more than four years beyond the doctorate. Applicants should not have previously served more than one postdoctoral appointment;
  • A proven academic record of high quality research with clear potential to perform cutting edge, high-impact, and innovative research in applied mathematics, statistics and/or computational science;
  • A rigorous Statement of Research, that provides the significance of your current research as well as the technical background of your proposed research at ORNL;
  • Three Letters of Reference, describing the applicants distinct contributions to their field of research, and;
  • The applicant must have a strong background and expertise in more than one area of particular relevance to the ORNL’s computational and applied mathematics program. 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 (SPDEs);
    • 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, and
    • 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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