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<p dir="LTR">The Mathematics and Computer Science (MCS) division at
Argonne National Laboratory seeks a Postdoctoral Appointee in
numerical optimization and machine learning to perform research in
developing theories, algorithms, and software libraries for
distributed optimization and learning algorithms. The successful
candidate will work as part of a multidisciplinary research team
involving computer <span><span class="WFN2">and computational</span></span> scientists,
mathematicians, and electrical engineers for data-driven
decision-making systems and analysis in various applications<span>. The
position will address algorithm/software development and/or
theory in areas of interest to the applied mathematics and
numerical software group. </span></p>
<p dir="LTR">The MCS Division at Argonne National Laboratory is a
leader in the domain of computer science, applied mathematics,
numerical software, and applications of interest to the U.S.
Department of Energy and various other agencies. Appointees will
participate in a collegial and stimulating environment, including
access to <span class="WFN2">multidisciplinary </span><span><span class="WFN2">collaborations, world-class software</span></span><span class="WFN2"> toolkits and</span> some of the world's largest
supercomputers including US's first exascale <span><span class="WFN2">supercomputer, "Aurora".</span></span></p>
<p dir="LTR"><b>Position Requirements</b></p>
<ul>
<li>PhD, completed or soon-to-be-completed (typically completed
within the last three years)</li>
<li><span>Candidates should have expertise in one or more of the
following areas: numerical optimization, large-scale
optimization, machine learning, and parallel and distributed
computing algorithms.</span></li>
<li><span>Considerable knowledge is also required in one or more
of the following areas: modeling, algorithms, and software
development in numerical optimization. </span></li>
<li><span>Good proficiency levels in scientific programming
languages (e.g., C, C++, Julia, Python) are also required. </span></li>
<li><span>Experience with Julia, Python, parallel computing,
large-scale computational science, machine learning, energy
systems is a plus.</span></li>
</ul>
<span>APPLY: </span><a href="https://bit.ly/3tZA1wP" title="Unmangled Microsoft Safelink">bit.ly/3tZA1wP</a><br>
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Kibaek Kim<br>
Argonne National Laboratory<br>
Lemont IL<br>
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