<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
<style type="text/css" style="display:none;"><!-- P {margin-top:0;margin-bottom:0;} --></style>
</head>
<body dir="ltr">
<div id="divtagdefaultwrapper" style="font-size:12pt;color:#000000;font-family:Calibri,Helvetica,sans-serif;" dir="ltr">
2 PHD POSITIONS ON COMPUTATIONAL VISION AT IIT – PAVIS IN COLLABORATION WITH UNIVERSITY OF GENOA, ITALY
<br>
<div style="color: rgb(0, 0, 0);">
<div>
<div id="divtagdefaultwrapper" dir="ltr" style="font-size:12pt; color:#000000; font-family:Calibri,Helvetica,sans-serif">
<div style="color:rgb(0,0,0)">
<div>
<div id="divtagdefaultwrapper" dir="ltr" style="font-size:12pt; color:rgb(0,0,0); font-family:Calibri,Helvetica,sans-serif,"EmojiFont","Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols">
<div><br>
The Italian Institute of Technology – IIT, www.iit.it – in collaboration with University of Genoa –https://unige.it/en – funds 2 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 http://phd-stiet.diten.unige.it/ and IIT infrastructures in Genoa,
<br>
at the PAVIS - Pattern Analysis and Computer Vision Research line https://pavis.iit.it/ led by its Principal Investigator, Alessio Del Bue.
<br>
<br>
RESEARCH TOPICS: <br>
Theme A: 3D scene understanding with geometrical and deep learning reasoning <br>
Theme B: Deep Learning for Multi-modal scene understanding <br>
Theme C: Self-Supervised and Unsupervised Deep Learning <br>
Theme D: Visual Reasoning with Knowledge and Graph Neural Networks <br>
<br>
Detailed description at: https://pavisdata.iit.it/data/phd/2023_ResearchTopicsPhD_IIT-PAVIS.pdf <br>
<br>
PAVIS <br>
The PhD program on the listed topics will take place at the PAVIS research line of IIT located in Genova (www.iit.it).
<br>
The department focuses 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>
PAVIS staff has a wide expertise in computer vision and pattern recognition, machine learning, image processing, and related applications (related to assistive and monitoring AI systems).
<br>
For more information, you can also browse the PAVIS webpage http://pavis.iit.it/ to see our activities and research.
<br>
<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 team, are mandatory.
<br>
<br>
HOW TO APPLY <br>
FULL INFORMATION, OFFICIAL CALL AND COURSE DESCRIPTION ARE AVAILABLE AT: <br>
ITALIAN <a href="https://unige.it/usg/it/dottorati-di-ricerca" class="OWAAutoLink" id="LPlnk946040" previewremoved="true">
https://unige.it/usg/it/dottorati-di-ricerca</a> <br>
ENGLISH <a href="https://unige.it/en/usg/en/phd-programmes" class="OWAAutoLink" id="LPlnk495164" previewremoved="true">
https://unige.it/en/usg/en/phd-programmes</a> <br>
</div>
<div><br>
Official call: https://unige.it/sites/contenuti.unige.it/files/documents/BANDO%2038%20CICLO%20-%20EN.pdf
<br>
Course description for XXXVIII Phd Course in Science and Technology for Electronic and Telecommunication Engineering, curriculum in Computer Vision, Automatic Recognition and Learning (CODE 9320) <br>
is on page 121 of the list of PhD programmes: https://unige.it/sites/contenuti.unige.it/files/documents/ALLEGATO_A_XXXVIII%20-%20EN.pdf <br>
<br>
Follow the steps listed: <br>
1. Choose the programme <br>
2. Review the application <br>
3. Apply here https://servizionline.unige.it/studenti/post-laurea/dottorato/domanda
<br>
following the detailed instructions: https://unige.it/sites/contenuti.unige.it/files/documents/Guida_eng_XXXVIII.pdf <br>
<br>
WHAT TO SUBMIT <br>
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 at pg. 121 of the course description document, above mentioned.
<br>
<br>
IMPORTANT: 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 https://pavisdata.iit.it/data/phd/ResearchProjectTemplate.pdf
<br>
For FURTHER INFORMATION on the research topics contact Dr. Del Bue at pavis@iit.it <br>
<br>
DEADLINE <br>
Deadline for application is June 30, 2022 at 12 PM (noon, Italian time/CEST) <br>
STRICT DEADLINE, NO EXTENSION. <br>
Apply before deadline, the application process is not immediate: don’t wait for the final day.
<br>
<br>
<br>
</div>
<br>
<div><br>
</div>
<br>
<p></p>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
</body>
</html>