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<p
style="margin-left:.375in;margin-top:6pt;margin-bottom:6pt;font-family:Arial;font-size:11.0pt"
lang="en-US">WIAS invites in the Research Group</p>
<p
style="margin-left:.375in;margin-top:6pt;margin-bottom:12pt;font-family:
Arial;font-size:12.0pt" lang="en-US"><span
style="font-weight:bold">“Nonsmooth
Variational Problems and Operator Equations”</span></p>
<p
style="margin-left:.375in;margin-top:0pt;margin-bottom:6pt;font-family:Arial;font-size:11.0pt"
lang="en-US">(Head: Prof. Dr. M. Hintermüller) applications for
a </p>
<p
style="margin:0in;margin-left:.375in;font-family:Arial;font-size:16.0pt"
lang="en-US"><span style="font-weight:bold">Research Assistant
Position (f/m/d) </span></p>
<p
style="margin:0in;margin-left:.375in;font-family:Arial;font-size:14.0pt"
lang="en-US"><span style="font-weight:bold">for data-driven and
variational
regularization methods for dynamic image reconstruction</span></p>
<p
style="margin-left:.375in;margin-top:0pt;margin-bottom:6pt;font-family:Arial;font-size:11.0pt"
lang="en-US"><span style="mso-spacerun:yes"> </span>(<span
style="font-weight:bold">Ref. 22/33</span>)</p>
<p
style="margin:0in;margin-left:.375in;font-family:Arial;font-size:11.0pt"
lang="en-US">to be filled at the earliest possible date. The
position is
associated to the MATH+ Cluster of Excellence EF3-12 project “<span
style="font-weight:bold">Integrated Learning and Variational
Methods for
Quantitative</span></p>
<p
style="margin:0in;margin-left:.375in;font-family:Arial;font-size:11.0pt"
lang="en-US"><span style="font-weight:bold">Dynamic Imaging</span>"
a joint
interdisciplinary project of the Weierstrass Institute for Applied
Analysis and
Stochastics (WIAS) and the Physikalisch-Technische Bundesanstalt
Institute
Berlin (PTB). </p>
<p
style="margin-left:.375in;margin-top:6pt;margin-bottom:6pt;font-family:Arial;font-size:11.0pt;color:black"
lang="en-US"><span style="font-weight:bold">The
work tasks include:</span></p>
<ul style="direction:ltr;unicode-bidi:embed;margin-top:0in;
margin-bottom:0in" type="disc">
<li
style="margin-top:0;margin-bottom:0;vertical-align:middle;margin-top:6pt;
margin-bottom:6pt" lang="en-US"><span
style="font-family:Arial;font-size: 11.0pt;color:black">Develop,
analyze and implement a spatio-temporal regularization
parameter learning framework for dynamic image reconstruction
with a particular focus on dynamic magnetic resonance imaging
(MRI)</span></li>
<li
style="margin-top:0;margin-bottom:0;vertical-align:middle;margin-top:6pt;
margin-bottom:6pt" lang="en-US"><span
style="font-family:Arial;font-size: 11.0pt;color:black">Develop
a machine learning framework for learning the physical law
processes that govern a MRI experiment and use this to enhance
existing and develop new numerical algorithms for quantitative
MRI</span></li>
<li
style="margin-top:0;margin-bottom:0;vertical-align:middle;margin-top:6pt;
margin-bottom:6pt" lang="en-US"><span
style="font-family:Arial;font-size: 11.0pt;color:black">Transfer
and evaluate the developed methods to clinical application
level along with the project partners</span></li>
</ul>
<p
style="margin-left:.375in;margin-top:6pt;margin-bottom:6pt;font-family:Arial;font-size:11.0pt;color:black"
lang="en-US"><span style="font-weight:bold">We are
looking for:</span> A motivated, outstanding researcher with a
very good degree
and excellent doctorate in mathematics as well as previous
experience in the
fields mentioned above.</p>
<p
style="margin-left:.375in;margin-top:6pt;margin-bottom:6pt;font-family:Arial;font-size:11.0pt;color:black"
lang="en-US">Additionally, it is highly desired
that the candidate has experience in:</p>
<ul style="direction:ltr;unicode-bidi:embed;margin-top:0in;
margin-bottom:0in" type="disc">
<li
style="margin-top:0;margin-bottom:0;vertical-align:middle;margin-top:6pt;
margin-bottom:6pt" lang="en-US"><span
style="font-family:Arial;font-size: 11.0pt;color:black">Mathematical
imaging, in particular variational as well as data-driven
regularization methods for image reconstruction</span></li>
<li
style="margin-top:0;margin-bottom:0;vertical-align:middle;margin-top:6pt;
margin-bottom:6pt" lang="en-US"><span
style="font-family:Arial;font-size: 11.0pt;color:black">Optimization
and optimal control with partial differential equations and
related numerical solution algorithms</span></li>
<li
style="margin-top:0;margin-bottom:0;vertical-align:middle;margin-top:6pt;
margin-bottom:6pt" lang="en-US"><span
style="font-family:Arial;font-size: 11.0pt;color:black">Scientific
computing and deep learning</span></li>
</ul>
<p
style="margin-left:.375in;margin-top:6pt;margin-bottom:6pt;font-family:Arial;font-size:11.0pt"
lang="en-US"><span style="color:black">Technical queries should
be directed to Prof. Dr. Michael Hintermüller
(<a class="moz-txt-link-abbreviated" href="mailto:Michael.Hintermueller@wias-berlin.de">Michael.Hintermueller@wias-berlin.de</a>). The position is
remunerated according
to TVöD Bund and is initially limited to two years.</span></p>
<p
style="margin-left:.375in;margin-top:6pt;margin-bottom:6pt;font-family:Arial;font-size:11.0pt;color:black"
lang="en-US">The Institute aims to increase the
proportion of women in this field, so applications from women are
particularly
welcome. Among equally qualified applicants, disabled candidates
will be given
preference.</p>
<p
style="margin-left:.375in;margin-top:6pt;margin-bottom:6pt;font-family:Arial;font-size:11.0pt"
lang="en-US"><span style="color:black">Please upload your
complete application documents, including cover letter,
curriculum vitae and
certificates, via our </span><a
href="https://short.sg/j/22772235">applicant
portal</a><span style="color:black"> as soon as possible but not
later than </span><span style="font-weight:bold;color:black">October 31</span><span
style="font-weight:bold;vertical-align:super;color:black">st</span><span
style="font-weight:bold;color:black">, 2022</span><span
style="color:black">
using the button "</span><a href="https://short.sg/a/22772235">Apply
online</a><span style="color:black">".</span></p>
<p
style="margin:0in;margin-left:.375in;font-family:Arial;font-size:11.0pt"
lang="en-US"><span style="font-weight:bold">We are looking forward
to your
application!</span></p>
<p
style="margin-left:.375in;margin-top:0pt;margin-bottom:6pt;font-family:Arial;font-size:11.0pt;color:black"> </p>
<p
style="margin:0in;margin-left:.375in;font-family:Arial;font-size:11.0pt"><span
style="font-weight:bold">See here for more information:<span
style="mso-spacerun:yes"> </span></span><a
href="https://short.sg/j/22772235" class="moz-txt-link-freetext">https://short.sg/j/22772235</a></p>
<pre class="moz-signature" cols="72">--
Administration
Weierstrass Institute for Applied Analysis and Stochastics
Mohrenstrasse 39
10117 Berlin, Germany
Phone: +49 (0)30 20372 557
Fax: +49 (0)30 20372 329
URL: <a class="moz-txt-link-freetext" href="http://www.wias-berlin.de/~sill/?lang=1">http://www.wias-berlin.de/~sill/?lang=1</a>
</pre>
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