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SAVG Postdoctoral Opportunities

This document describes National Research Council Postdoctoral Research Associateships tenable within the Scientific Applications and Visualization Group.

(bullet) Judith E. Terrill (NIST/MCSD/SAVG)

NIST scientists are currently automating experiments resulting in increasing amounts of generated data in multidimensional spaces. The data come primarily from combinatorial experiments in materials science. This type of data consists of image data with additional measurements at each pixel. Other experiments result in spectra-like measurements taken over spatial domains. These datasets require techniques that can sift through large amounts of data for items of potential interest, as well as for discovery. We are collaborating with these scientists on ways to mine this data for scientific insight. Opportunities exist for the application of datamining techniques such as classification, rule finding, and automated model building to these datasets, as well as for the development of new techniques.


(bullet) William L. George (NIST/MCSD/SAVG)

As the size and computational power of parallel and distributed computing systems increase, it is important to continually investigate the appropriateness of the algorithms we use for our scientific applications. Although we always strive to design and build scalable parallel applications, we must re-think these deigns when the available computational resources increase in power by even as small as a single order of magnitude with respect to the number of processors, main memory size, network speed, or other relevant parameters. This research opportunity focuses on (1) investigating and developing new parallel algorithms, especially for scientific applications, for the next generation of computing platforms; (2) characterizing the programming models presented by new parallel and distributed computing platforms; (3) investigating the design and performance of parallel programming languages and libraries; and (4) investigating the role of web services, fourth generation languages such as Matlab and Mathematica, computational grids, and other developing technologies in providing novel high-performance computing environments.


(bullet) Judith E. Terrill (NIST/MCSD/SAVG)

With the continuing increase in speed and capability of commodity graphics processors, immersive visualization offers increasing opportunities to express scientifically meaningful results. Data at NIST spans a wide range from nano to cement to models that exhibit complex dynamics. This research will build on our open source software that runs on a linux desktop as well as immersively. Opportunities exist for 1) investigating the use of immersive visualization as a scientific instrument for exploration and representation of data, 2) developing ways to merge analysis with visualization and provide quantitative feedback into the visualization, 3) exploring and expressing uncertainties, 4) harnessing the growing capability of graphics processors to provide insight, 5) advancing the use of abstraction to express meaning in data, 6) developing user interaction methods, including direct manipulation techniques.


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Last updated: 2011-01-12.