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<th valign="BASELINE" nowrap="nowrap" align="RIGHT">Subject:
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<td>PhD position: Normalizing Flows and Their Applications
in Precision Physics and Applied Mathematics</td>
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<th valign="BASELINE" nowrap="nowrap" align="RIGHT">Date: </th>
<td>Thu, 6 Oct 2022 11:56:55 +0200</td>
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<th valign="BASELINE" nowrap="nowrap" align="RIGHT">From: </th>
<td>Johannes Lange <a class="moz-txt-link-rfc2396E" href="mailto:johannes.lange@cern.ch"><johannes.lange@cern.ch></a></td>
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<th valign="BASELINE" nowrap="nowrap" align="RIGHT">To: </th>
<td><a class="moz-txt-link-abbreviated" href="mailto:lhc-machinelearning-wg@cern.ch">lhc-machinelearning-wg@cern.ch</a></td>
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<br>
Dear all,<br>
<br>
we have an open position at Hamburg University (CMS group), shared
with the Hamburg University of Technology via the DASHH graduate
school, for a PhD student to work on the topic of normalizing flow
networks and applications in HEP measurements and searches. You
can find a short description below.<br>
All details and the application form can be found here:<br>
<a class="moz-txt-link-freetext" href="https://www.dashh.org/application/phd_topics/normalizing_flows_in_precision_physics/index_eng.html">https://www.dashh.org/application/phd_topics/normalizing_flows_in_precision_physics/index_eng.html</a><br>
<br>
It would be nice if you could forward this information to
interested candidates.<br>
<br>
Best,<br>
Johannes<br>
<br>
<br>
<br>
### Short description<br>
The aim of the project is the development of deep normalizing flow
networks (NFs) to obtain probability densities of stochastic data
and demonstrate their usage in precision measurements and searches
for new interactions in particle collisions at highest energies,
as well as for inversion problems.<br>
<br>
While deep neural networks are by now routinely used in most
classification problems in particle physics, their usage is still
limited since the understanding of the network response in terms
of likelihoods is most of the time unknown. Likelihood-based
estimation however is the standard working horse for both
precision measurements of fundamental parameters (e.g. top quark
mass) and for searches of rare processes (e.g. triple-Higgs
interactions), where only a few measured events dominate the
sensitivity. The NF approach can be a game changer towards
interpretable neural networks for many applications. This however
requires research for multiclass applications, uncertainty
estimation, and inversion properties.<br>
<br>
### Requirements<br>
In order to apply you need to have a Master's Degree (or an
estimated date of Graduation within the same year of application)
in computer science, applied mathematics or natural sciences,
preferably with an interdisciplinary training at the interface of
natural and computer science or mathematics. Degrees from foreign
universities and master degrees in non-research oriented study
programs (Fachhochschule) might be eligible. For further
information, consult the doctorate regulations (Promotionsordnung)
of the respective partner university.<br>
<br>
Full details can be found here:<br>
<a class="moz-txt-link-freetext" href="https://www.dashh.org/application/requirements/index_eng.html">https://www.dashh.org/application/requirements/index_eng.html</a><br>
<br>
### Application form<br>
Follow the "Apply"-link here:<br>
<a class="moz-txt-link-freetext" href="https://www.dashh.org/application/phd_topics/normalizing_flows_in_precision_physics/index_eng.html">https://www.dashh.org/application/phd_topics/normalizing_flows_in_precision_physics/index_eng.html</a><br>
<br>
### Contact<br>
In case of questions, do not hesitate to contact either<br>
Prof. Peter Schleper, UHH (<a class="moz-txt-link-abbreviated" href="mailto:peter.schleper@uni-hamburg.de">peter.schleper@uni-hamburg.de</a>)<br>
Prof. Daniel Ruprecht, TUHH (<a class="moz-txt-link-abbreviated" href="mailto:ruprecht@tuhh.de">ruprecht@tuhh.de</a>)<br>
or myself, UHH (<a class="moz-txt-link-abbreviated" href="mailto:johannes.lange@uni-hamburg.de">johannes.lange@uni-hamburg.de</a>).<br>
<br>
<br>
<pre class="moz-signature">--
Dr. Johannes Lange
Institut für Experimentalphysik | Universität Hamburg
Luruper Chaussee 149 | 22761 Hamburg | Germany
Phone: +49 (0)40 8998 - 2115 | Office: 68/112
</pre>
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