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      -------- Forwarded Message --------
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            <th valign="BASELINE" nowrap="nowrap" align="RIGHT">Subject:
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            <td>open positions phd/post-doc on generative models
              (UNIGE/UAS-WS)</td>
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            <th valign="BASELINE" nowrap="nowrap" align="RIGHT">Resent-From:
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            <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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            <th valign="BASELINE" nowrap="nowrap" align="RIGHT">Date: </th>
            <td>Fri, 10 Jun 2022 16:07:27 +0200</td>
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            <th valign="BASELINE" nowrap="nowrap" align="RIGHT">From: </th>
            <td>Alexandros Kalousis <a class="moz-txt-link-rfc2396E" href="mailto:alexandros.kalousis@unige.ch"><alexandros.kalousis@unige.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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        <p>Dear all, <br>
        </p>
        <p>Apologies for spamming the list with something not directly
          related to ml and physics.<br>
        </p>
        We have a couple of SNSF funded open positions (phd/post-doc) on
        generative models for discrete data structures with a focus on
        molecule generation, funding available for four years, for more
        details please see here:
        <p>​<a class="moz-txt-link-freetext" href="http://dmml.ch/post-doc-position-on-generative-models-for-discrete-data-structures/">http://dmml.ch/post-doc-position-on-generative-models-for-discrete-data-structures/</a></p>
        <p><a class="moz-txt-link-freetext" href="http://dmml.ch/phd-position-on-generative-models-for-discrete-data-structures/">http://dmml.ch/phd-position-on-generative-models-for-discrete-data-structures/</a></p>
        <p>Of more relevance to the list might be two additional
          positions (phd/post-doc) which will open very soon on
          generative models for inverse problems and simulation-based
          inference. This is in the context of a collaborative project
          that brings together geology, seismology and machine learning,
          to streamline the passive seismic exploration methods for
          geothermal exploration. The main technical goal is to invert
          the surface wave ambient noise tomography imaging in order to
          <span><span>the <span>subsurface velocity structure of the
                Earth's upper crust</span>. </span></span></p>
        For more details please contact me at
        <a class="moz-txt-link-abbreviated" href="mailto:Alexandros.Kalousis@hesge.ch">Alexandros.Kalousis@hesge.ch</a>
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        <p>best, <br>
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        <p>Alexandros<br>
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