<html><head><meta http-equiv="Content-Type" content="text/html charset=windows-1252"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; "><div apple-content-edited="true"><div style="color: rgb(0, 0, 0); font-family: Helvetica; font-size: medium; font-style: normal; font-variant: normal; font-weight: normal; letter-spacing: normal; line-height: normal; orphans: 2; text-align: -webkit-auto; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; "><div><div>Postdoc Position in Optimization and Multiscale Analysis of Energy Materials</div><div><p class="MsoListParagraph" style="margin-left: 0in; text-align: justify; ">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<o:p></o:p></p><p class="MsoNormal"><o:p> </o:p><span style="text-align: justify; ">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.</span></p><div>For further information about this position and the application process, please see </div><div><a href="http://web.anl.gov/jobsearch/detail.jsp?userreqid=320357+MCS">http://web.anl.gov/jobsearch/detail.jsp?userreqid=320357+MCS</a></div><div><br></div><div>Sven Leyffer, Todd Munson, and Stefan Wild</div><div>MCS Division, Argonne National Laboratory</div></div></div><div><br></div></div><br class="Apple-interchange-newline"><br class="Apple-interchange-newline">
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