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        id="docs-internal-guid-698b607f-7fff-3802-5151-2a3e0ef64236"><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:#f9fafb;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Multiple positions at post-doctoral level are available in the Department of Computer Science at the University of Trento (UniTN), to work under the supervision of Prof. Nicu Sebe (</span><a
          href="http://disi.unitn.it/~sebe/"
          style="text-decoration:none;" moz-do-not-send="true"><span style="font-size:10pt;font-family:Arial;color:#4a86e8;background-color:#f9fafb;font-weight:400;font-style:normal;font-variant:normal;text-decoration:underline;-webkit-text-decoration-skip:none;text-decoration-skip-ink:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">http://disi.unitn.it/~sebe</span><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:#f9fafb;font-weight:400;font-style:normal;font-variant:normal;text-decoration:underline;-webkit-text-decoration-skip:none;text-decoration-skip-ink:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">/</span></a><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:#f9fafb;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">) and Prof. Elisa Ricci (</span><a
          href="http://elisaricci.eu" style="text-decoration:none;"
          moz-do-not-send="true"><span style="font-size:10pt;font-family:Arial;color:#4a86e8;background-color:#f9fafb;font-weight:400;font-style:normal;font-variant:normal;text-decoration:underline;-webkit-text-decoration-skip:none;text-decoration-skip-ink:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">http://elisaricci.eu</span></a><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:#f9fafb;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">).</span></p>
      <p dir="ltr"
        style="line-height:1.2;margin-top:12pt;margin-bottom:0pt;"><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:#f9fafb;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">The candidates will join the MHUG (Multimedia and Human Understanding Group) at UniTN and be part of the Vision and Learning Joint Laboratory, a new laboratory bringing together computer vision researchers from UniTN and Fondazione Bruno Kessler (</span><a
          href="https://www.fbk.eu/" style="text-decoration:none;"
          moz-do-not-send="true"><span style="font-size:10pt;font-family:Arial;color:#4a86e8;background-color:#f9fafb;font-weight:400;font-style:normal;font-variant:normal;text-decoration:underline;-webkit-text-decoration-skip:none;text-decoration-skip-ink:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">https://www.fbk.eu</span></a><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:#f9fafb;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">). The research group conducts research in the fields of computer vision and multimedia. In computer vision, we address a large spectrum of themes including human-behavior analysis, action recognition, 2D/3D object detection, large-scale event detection and video analysis, etc.  In multimedia, our research focuses on cross media retrieval, multi-modal learning, social media analysis, emotion recognition, etc.</span></p>
      <p dir="ltr"
        style="line-height:1.2;margin-top:12pt;margin-bottom:0pt;"><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">The open positions are financed by several projects: the H2020 EU Project SPRING (Socially Assistive Robots for Gerontological Healthcare), the PRIN italian project PREVUE (Prediction of Activities and Events by Vision in an Urban Environment), EUREGIO project OLIVER (Open-ended Learning for Interactive Robots), and collaboration project Italy-CHINA TALENT (Joint UAV and Surveillance Video Content Analysis and Mining for Smart City). The research group is also involved in several industrial projects, in collaboration with many national and international companies.</span></p>
      <p dir="ltr"
        style="line-height:1.2;margin-top:12pt;margin-bottom:0pt;"><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">The main research themes are:</span></p>
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        <li dir="ltr" style="list-style-type:disc;font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;"><p dir="ltr" style="line-height:1.38;margin-top:12pt;margin-bottom:0pt;"><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Theme A: </span><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:underline;-webkit-text-decoration-skip:none;text-decoration-skip-ink:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Human Behavior Analysis</span><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">. The activity will focus on designing novel algorithms and models for analyzing and understanding human behavior from visual data gathered by a robotic platform. Specifically, we expect the candidate to develop algorithms for behavioral cues extraction  (e.g. gestures, facial expressions), human action recognition/anticipation and social interactions analysis. </span><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">    </span><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;"> </span><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">    </span></p></li>
        <li dir="ltr" style="list-style-type:disc;font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Theme B: </span><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:underline;-webkit-text-decoration-skip:none;text-decoration-skip-ink:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Semantic Scene Understanding</span><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">. The activity will focus on developing deep learning-based algorithms for semantic scene analysis. In particular, the research activity will focus on devising algorithmic solutions for pixel-level prediction tasks (e.g. semantic segmentation, depth estimation) and on their integration within tools for building semantic maps of indoor scenes. </span></p></li>
        <li dir="ltr" style="list-style-type:disc;font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:12pt;"><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Theme C: </span><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:underline;-webkit-text-decoration-skip:none;text-decoration-skip-ink:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Domain Adaptation and Continual Learning</span><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">. The activity will build on previous works from the research group (Mancini </span><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:italic;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">et al.</span><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">, CVPR 2019; Berriel </span><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:italic;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">et al.</span><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">, ICCV 2019, Roy </span><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:italic;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">et al.</span><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;"> CVPR 2019) and will focus on devising novel algorithms for domain adaptation and continual learning, with special emphasis on methodologies for video streams analysis. </span><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">

</span></p></li>
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        style="line-height:1.38;margin-top:12pt;margin-bottom:12pt;"><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">The candidates </span><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:#ffffff;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">are expected to take a lead role in the projects, including developing novel algorithmic solutions, setting up experiments, collecting and analyzing data, training and supervision of graduate students and undergraduate research assistants, and dissemination of results at conferences and in research publications. </span></p>
      <p dir="ltr"
        style="line-height:1.2;margin-top:12pt;margin-bottom:0pt;"><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">At the time of the application, eligible candidates should have a Ph.D. degree in Computer Science, Engineering, or related fields. Proven scientific track record on major computer vision and multimedia conferences/journals (CVPR, ICCV, ECCV, ACM Multimedia, TPAMI, IJCV, etc.) is a criteria for the selection as well as experience on </span><span style="font-size:11pt;font-family:Calibri,sans-serif;color:#222222;background-color:#ffffff;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">deep learning algorithms and relevant platforms (e.g. TensorFlow, PyTorch, Theano, Caffe)</span><span style="font-size:10pt;font-family:Arial;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">. Experience in robotics is considered a plus. Desirable skills and qualifications are </span><span style="font-size:11pt;font-family:Calibri,sans-serif;color:#222222;background-color:#ffffff;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">experience in grant proposal preparation at European and National level as well as experience in supervising or co-supervising PhD and MSc students. 
</span></p>
      <pre class="moz-signature" cols="72">-- 
Prof. Nicu Sebe, Ph.D. 
Department of Information Engineering and Computer Science
University of Trento
Via Sommarive 9 - 38123 Povo - Trento (Italy)

ph. + 39 0461 28 2989
fax. + 39 0461 28 3939
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