[visionlist] 2 PHD POSITIONS ON COMPUTER VISION AT IIT PAVIS IN COLLABORATION WITH UNIVERSITY OF GENOA, ITALY

Pavis Pavis at iit.it
Wed May 12 10:07:42 -04 2021


2 PHD POSITIONS ON COMPUTER VISION AT IIT – PAVIS IN COLLABORATION WITH UNIVERSITY OF GENOA, ITALY
IIT, Italian Institute of Technology - www.iit.it,  in collaboration with University of Genoa - https://unige.it/en funds 2 PhD scholarships on Computer Vision, Pattern Recognition and Machine Learning.
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,
at the PAVIS - Pattern Analysis and Computer Vision Research line https://pavis.iit.it/ led by its Principal Investigator, Alessio Del Bue - https://www.iit.it/it/people-details/-/people/alessio-delbue

RESEARCH TOPICS:
Theme A: 3D scene understanding with geometrical and deep learning reasoning
Theme B: Artificial Intelligence for Human Behavior Analysis
Theme C: Deep Learning for Multi-modal scene understanding
Theme D: Self-Supervised and Unsupervised Deep Learning
Theme E: Visual Reasoning with Knowledge and Graph Neural Networks for scene understanding

Detailed description at:  https://pavisdata.iit.it/data/phd/2022_PhD_research_topics_PAVIS_IIT.pdf

PAVIS
The PhD program on the listed topics will take place at the PAVIS research line of Istituto Italiano di Tecnologia (IIT) located in Genova (www.iit.it).
The department focuses on activities related to the analysis and understanding of images, videos and patterns in general, even multidisciplinary, in collaboration with other research groups in IIT.
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).
For more information, you can also browse the PAVIS webpage http://pavis.iit.it/ to see our activities and research.
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.
Excellent communication skills in English, as well as ability to interact effectively with members of the research team, are mandatory.


HOW TO APPLY
Full information, official call and course description are available at
ITALIAN https://unige.it/usg/it/dottorati-di-ricerca
ENGLISH https://unige.it/en/usg/en/phd-programmes
Official call: https://unige.it/sites/contenuti.unige.it/files/documents/Bando_XXXVII_English.pdf
Course description for XXXVII Phd Course in Science and Technology for Electronic and Telecommunication Engineering, curriculum in Computer Vision, Pattern Recognition and Machine Learning (CODE 8718)
is on page 108 of the list of PhD programmes: https://unige.it/sites/contenuti.unige.it/files/documents/ANNEX_A_XXXVII%20-%20EN_0.pdf
Please follow the steps listed:
1. Choose the programme, 2. Review the application, 3. Apply, following the detailed instructions
https://unige.it/sites/contenuti.unige.it/files/documents/Guida_eng_XXXVII.pdf
and using the online procedure
https://servizionline.unige.it/studenti/post-laurea/dottorato/domanda

WHAT TO SUBMIT
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.
Notice that these documents are mandatory in order to consider valid the application.
Refer also to the indications stated at pg. 108 of the course description document, above mentioned.
IMPORTANT: In order to apply, candidates must prepare the research proposal based on the research topics above mentioned.
Please, follow these indications to prepare it https://pavisdata.iit.it/data/phd/ResearchProjectTemplate.pdf
For FURTHER INFORMATION on the research topics contact Dr. Del Bue at pavis at iit.it

DEADLINE
Deadline for application is June 15, 2021 at 12 PM (noon, Italian time/CEST)
STRICT DEADLINE, NO EXTENSION.
Apply before deadline, the application process is not immediate: don’t wait for the final day.



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