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2 open postdoc positions in data analysis and visualization

 

319355: Postdoctoral Position in Data-intensive Analysis, Visualization, and Storage
This computer science postdoc will conduct basic and applied research in parallel and scalable algorithms for data analysis and visualization on HPC architecture, data models for storage and analysis of scientific data, and integration of methods in parallel scientific simulations. He or she will work as part of an integrated, multidisciplinary research team and will collaborate with computer and computational scientists at Argonne as well as in the broader community. The ideal candidate will have comprehensive knowledge in C/C++ programming under Unix/Linux, and experience in data analysis and/or scientific visualization, including one or more of the following: statistical analysis, graph analysis, data mining, visualization of scalar and vector multivariate data. Experience in software development for parallel computing is a plus. Candidates should have earned a Ph.D. in computer science within the past three years. 
 
To apply:
 
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321176: Postdoctoral Position in Data Analysis and Visualization of Superconductivity
We seek a postdoc in computer science to analyze and visualize simulations of superconductivity at Argonne National Laboratory. The successful candidate will work as part of a multidisciplinary research team involving physicists, computer scientists, and mathematicians to detect and track the temporal evolution of vortex dynamics in superconductors.  The postdoc will collaborate with members of the SciDAC SDAV Institute (http://www.sdav-scidac.org) and OSCon partnership (http://oscon-scidac.org) to detect, track, and view features at scale from large amounts of data in situ and in postprocessing. Algorithms will leverage multi-core/GPU clusters and DOE Advanced Scientific Computing Research supercomputing facilities. The ideal candidate will have comprehensive knowledge in C/C++ programming under Unix/Linux, and experience in data analysis and/or scientific visualization, including one or more of the following: topological analysis, feature detection, feature tracking, visualization of scalar and vector multivariate data. Experience in software development for parallel computing is a plus. Candidates should have earned a Ph.D. in computer science within the past three years.
 
To apply:
 
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