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    <p><strong>Call for SMASH Marie SkÅ‚odowska-Curie Computer Vision
        postdoc</strong><span class="white-space-pre"> </span><strong>applications</strong></p>
    <span>
      <p><strong>Description:</strong><br>
        SMASH MSCA program offers 2-year full-time fellowship, which
        includes generous research and travel funds and a salary
        comparable to a full professor. The program funds high-quality
        postdoctoral projects in a few selected universities <span>(project
          submisison deadline 1.4.2025)</span>. Accepted candidates
        offered to spend part of postdoc at secondments. More details
        here:<a href="https://smash.ung.si/open-call-4/" class="moz-txt-link-freetext">
          https://smash.ung.si/open-call-4/</a>.<span class="white-space-pre"> </span></p>
      <p><span><strong>Where:</strong><br>
          Visual Cognitive Systems Laboratory, University of Ljubljana,
          Slovenia. The postdocs will work under supervision of prof.
          Matej Kristan (<a href="https://www.vicos.si/people/matej_kristan/" class="moz-txt-link-freetext">https://www.vicos.si/people/matej_kristan/</a>).</span></p>
      <p><span>
          <p><strong>Relevant topics:</strong></p>
          <ul>
            <li>Machine learning for extreme weather (computer vision
              methods for weather prediction and geophysics -- see some
              <a href="https://www.vicos.si/research/hidra/">recent
                publications on the topic</a> for more details.)</li>
            <li><span>Computer vision </span></li>
          </ul>
        </span></p>
      <p><strong>Interested candidates</strong><br>
        The interested candidates should send their expression of
        interest (a single pdf) to <i><a class="moz-txt-link-abbreviated moz-txt-link-freetext" href="mailto:matej.kristan@fri.uni-lj.si">matej.kristan@fri.uni-lj.si</a></i>
        including:</p>
      <ul>
        <li>(i) a research statement briefly outlining your past
          research and the topic of interest,</li>
        <li>(ii) CV highlighting computer vision and/or deep learning
          experience with a strong publication record,</li>
        <li>(iii) names of two referees willing to provide support
          letters.</li>
      </ul>
      <p><span>
          <p><strong>Qualifications:</strong></p>
          <ul>
            <li>PhD in Computer Science or a related field (computer
              vision or machine learning) or physics.</li>
            <li>Strong background in deep learning and computer vision.</li>
            <li>Proficiency in programming languages such as Python and
              frameworks such as TensorFlow or PyTorch.</li>
            <li>Strong written and oral communication skills.</li>
            <li>Strong publication record.</li>
          </ul>
        </span></p>
      <p>Following an interview with the potential supervisor, the
        selected candidates will be <span> required to submit a short
          (10 pages) research proposal to SMASH </span><span><span><span>for
              the nomination</span></span>. The proposal and the
          candidates will be reviewed by external panel. Upon </span><span>successfully
          securing funds, the will be enrolled in the program.</span><span></span></p>
    </span><span>
      <p><strong>Important dates:</strong></p>
      <ul>
        <li>1.3.2025 Deadline for expression of interest to Matej
          Kristan.</li>
        <li>1.4.2025 SMASH application deadline for selected candidates.</li>
      </ul>
    </span>
    <p></p>
    <pre class="moz-signature" cols="72">-- 
Prof. Matej Kristan                         | Visual Cognitive Systems Lab
<a class="moz-txt-link-freetext" href="https://www.vicos.si/people/matej_kristan/">https://www.vicos.si/people/matej_kristan/</a>  | Faculty of Computer and Information Science
Tel: +386 1 479 8245                        | University of Ljubljana

"If the world should blow itself up, the last audible voice would be that of an expert saying it can't be done."
(Peter Ustinov)</pre>
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