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. This is one of ORNL’s most prestigious postdoctoral fellowships with funding from the Applied Mathematics Research Program in the U.S. Department of Energy’s Office of Advanced Scientific Computing Research.
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.
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.