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Postdoc Position in Optimization and Multiscale Analysis of Energy Materials

The Mathematics and Computer Science (MCS) Division at Argonne
National Laboratory invites outstanding candidates to apply for a
postdoctoral position to develop mathematical/algorithmic approaches
for merging engineering multiscale data arising in tomography and
fluorescence experiments from the Advanced Photon Source (APS). This
task includes the development of mathematical models for merging
multiscale data, extending image registration techniques based on
PDE-constrained optimization to bridge scales, and implementing these
methods in scalable libraries, such as Argonne’s Toolkit for Advanced
Optimization (TAO). The postdoc will also interact with APS scientists
and with computer scientists at MCS on data-related topics such as
parallel data models

The appointment will be in the Mathematics and Computer Science
Division, which has strong programs in scientific computing, software
tools, and computational mathematics. Candidates should be familiar
with C/C++ and have a background in one or more of the following:
optimization, scientific computing, data analysis, and machine
learning. Experience with parallel toolkits such as PETSc, or
large-scale optimization is a plus.

For further information about this position and the application
process, please see
http://web.anl.gov/jobsearch/detail.jsp?userreqid=320357+MCS

Sven Leyffer, Todd Munson, and Stefan Wild
MCS Division, Argonne National Laboratory

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