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<font face="Candara"><b>APOLOGIES FOR MULTIPLE POSTINGS<br>
</b>================================<br>
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<p class="xmsonormal"><b><span lang="EN-US" style="font-family:"Calibri",sans-serif;color:black">PHD
POSITIONS ON COMPUTATIONAL VISION AND MACHINE LEARNING AT IIT
– </span></b><b><span lang="EN-US" style="font-family:"Calibri",sans-serif">AIGO, <span style="color:black"></span><span style="color:black">IN
COLLABORATION WITH UNIVERSITY OF GENOA, ITALY </span></span></b><span lang="EN-US"></span></p>
The Italian Institute of Technology – IIT, <a href="https://www.iit.it" moz-do-not-send="true">www.iit.it</a> –
in collaboration with University of Genoa, <a href="https://unige.it/en" class="moz-txt-link-freetext" moz-do-not-send="true">https://unige.it/en</a> – funds PhD
scholarships on Computational Vision, Automatic Recognition and
Learning. <br>
<br>
Research and training activities are jointly conducted between the
DITEN Department of University of Genova <a class="moz-txt-link-freetext" href="http://phd-stiet.diten.unige.it/" moz-do-not-send="true">http://phd-stiet.diten.unige.it/</a>
and IIT infrastructures in Genoa, at the AIGO – AI for Good - <a href="https://aigo.iit.it" class="moz-txt-link-freetext" moz-do-not-send="true">https://aigo.iit.it</a>, led by prof.
Vittorio Murino.<br>
<br>
<br>
<b>RESEARCH TOPICS<br>
</b><b>AIGO Themes range from A to L:<br>
</b>Theme A: Disentangled Representation Learning via Diffusion
Models<br>
Theme B: Continual generalized category discovery , incremental
learning<br>
Theme C: Advancing Temporal Multimodal Understanding through
Prompt-Adaptive MLLMs<br>
Theme D: Unlearning in Multimodal Healthcare Data<br>
Theme E: Multimodal scene understanding<br>
Theme F: Few-shot Anomaly Detection in Medical Data<br>
Theme G: Discovery and mitigate bias in deep neural networks <br>
Theme H: Federated Learning by multimodal generative modeling<br>
Theme I: Biomedical imaging & Neuroimaging<br>
Theme L: Computer vision into the wild<br>
<br>
More detailed information on the specific themes and indication of
supervisors, at <br>
<a href="https://pavisdata.iit.it/data/phd/ResearchTopicsPhD_2025_2026_IIT-AIGO_PAVIS.pdf" moz-do-not-send="true">https://pavisdata.iit.it/data/phd/ResearchTopicsPhD_2025_2026_IIT-AIGO_PAVIS.pdf<br>
</a><br>
AIGO is a recently born research unit focusing on activities related
to the analysis and understanding of images, videos and patterns in
general, also in collaboration with other research groups at IIT. <br>
AIGO main focus is the learning with imperfect data, meaning in
unsupervised, semi-supervised and self-supervised scenarios, noisy
labeling, biased data and imbalanced classes.<br>
AIGO staff has a wide expertise in computer vision and pattern
recognition, machine and deep learning, image processing, and
related applications, especially, but not limited to, of
biomedical/biological nature. Multimodal and generative learning are
other keywords characterizing AIGO activities.<br>
For more information, you can also browse prof. Murino webpage, to
see his activities and research.<br>
<br>
<br>
<b>WHERE<br>
</b>The PhD program on the listed topics will take place at the
research line of IIT located in Genova, Italy (<a href="www.iit.it" class="moz-txt-link-freetext" moz-do-not-send="true">www.iit.it</a>)<br>
Successful candidates will be part of an exciting and international
working environment and will work in brand new laboratories equipped
with state-of-the-art instrumentation. <br>
Excellent communication skills in English, as well as ability to
interact effectively with members of the research teams, are
mandatory.<br>
<br>
<br>
<b>HOW TO APPLY<br>
</b>Full information, official call and course description are
available at <br>
ITALIAN <a href="https://unige.it/dottorati-di-ricerca" class="moz-txt-link-freetext" moz-do-not-send="true">https://unige.it/dottorati-di-ricerca</a><br>
ENGLISH <a href="https://unige.it/dottorati-di-ricerca" moz-do-not-send="true">https://unige.it/en/students/phd-programmes</a><br>
<br>
Official call: <a class="moz-txt-link-freetext" href="https://unige.it/sites/unige.it/files/2025-06/Notice%20of%20competition.pdf" moz-do-not-send="true">https://unige.it/sites/unige.it/files/2025-06/Notice%20of%20competition.pdf</a><br>
Course: SCIENCE AND TECHNOLOGY FOR ELECTRONIC AND TELECOMMUNICATION
ENGINEERING<br>
Curriculum: COMPUTATIONAL VISION, AUTOMATIC RECOGNITION AND LEARNING
(CODE 11254)<br>
Annex A: <a href="https://unige.it/sites/unige.it/files/2025-06/Annex%20A.pdf" class="moz-txt-link-freetext" moz-do-not-send="true">https://unige.it/sites/unige.it/files/2025-06/Annex%20A.pdf</a>
<br>
The candidate can easily find the right curriculum to apply by
searching the word "Murino" in the Annex A pdf document<br>
<br>
<b>Apply for the position: <br>
</b><a href="https://unige.it/en/students/phd-programmes" class="moz-txt-link-freetext" moz-do-not-send="true">https://unige.it/en/students/phd-programmes</a>
<br>
(follow Step 3)<br>
<br>
<br>
<b>WHAT TO SUBMIT<br>
</b>A detailed CV, a research proposal under one or more topics
chosen among those above indicated, reference letters, and any other
formal document concerning the degrees earned. <br>
Notice that these documents are mandatory in order to consider valid
the application.<br>
Refer also to the indications stated in the course description
document, above mentioned.<br>
<br>
<b>IMPORTANT:</b> In order to apply, candidates must prepare the
research proposal based on the research topics above mentioned. <br>
Please, follow these indications to prepare it: <br>
<a href="https://pavisdata.iit.it/data/phd/ResearchProjectTemplate.pdf" moz-do-not-send="true">https://pavisdata.iit.it/data/phd/ResearchProjectTemplate.pdf<br>
</a><br>
For FURTHER INFORMATION on the research topics contact Vittorio
Murino at <a href="mailto:vittorio.murino@iit.it" moz-do-not-send="true" class="moz-txt-link-freetext">vittorio.murino@iit.it</a><br>
<br>
<br>
<br>
<b>DEADLINE<br>
</b>Deadline for application is July 9, 2025 at 12 PM (noon, Italian
time/CEST) <br>
<br>
============================ <span lang="EN-US"></span>
<pre class="moz-signature" cols="72">--
Vittorio
*******************************************
Prof. Vittorio Murino, Ph.D.
AIGO -- AI for Good
Istituto Italiano di Tecnologia
via Enrico Melen 83, Building B, Floor 8
16152 Genova, Italy
Mobile: +39 329 6508554
E-mail: <a class="moz-txt-link-abbreviated moz-txt-link-freetext" href="mailto:vittorio.murino@iit.it" moz-do-not-send="true">vittorio.murino@iit.it</a>
<a class="moz-txt-link-freetext" href="https://www.vittoriomurino.com" moz-do-not-send="true">https://www.vittoriomurino.com</a>
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