6 PHD POSITIONS ON COMPUTER VISION AT IIT – PAVIS IN COLLABORATION WITH UNIVERSITÀ DEGLI STUDI DI GENOVA - [ PhD ]

Workplace: Genova, IIT
Added on: 18/05/2020 - Expires on: 15/06/2020

6 PhD Positions

IIT has established a collaboration with Università degli studi di Genova and funds 6 PhD scholarships on Computer Vision and Machine Learning.

Research and training activities are jointly conducted between the DITEN Department of University and IIT infrastructures in Genoa, at the PAVIS - Pattern Analysis and Computer Vision Research line, led by its Principal Investigator, Alessio Del Bue.

 

RESEARCH TOPICS:

Theme A - 3D scene understanding with geometrical and deep learning reasoning

Theme B - Artificial Intelligence for Human Behavior Analysis

Theme C - People and Object Re-identification in the wild

Theme D - Deep Learning for Multi-modal scene understanding

Theme E - Weakly Supervised and Unsupervised Deep Learning

Theme F - Visual Reasoning with Knowledge and Graph Neural Networks for scene understanding  

Theme G - Distributed AI in sensor networks and robotic platforms

 

Detailed description at: https://pavisdata.iit.it/data/phd/ResearchTopics2021_IIT-PAVIS

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

In order to apply for the XXXVI Phd Course in Science and Technologies for Electronics and Telecommunication Engineering, curriculum in Computer Vision, Pattern Recognition and Machine Learning (CODE 8259) it is mandatory to refer to the procedures administered by Università degli studi di Genova.

The official call (bando di concorso) is available at this link: https://unige.it/usg/it/dottorati-di-ricerca, where the call and the annex A (allegato A) are available For the english version, see: https://unige.it/en/usg/en/phd-programmes

APPLICATIONS are already possible through University of Genoa ONLINE PROCEDURE ONLY:

http://servizionline.unige.it/studenti/post-laurea/dottorato

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 in the annex A 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@iit.it

DEADLINE

ONLINE APPLICATION DEADLINE is JUNE 15, 2020 at 12:00 p.m. (noon, Italian time/CEST) – STRICT DEADLINE, NO EXTENSION.

Apply before deadline, the application process is not immediate: don’t wait for the final day.

Contacts
Involved Research lines
Pattern Analysis and Computer Vision Visual Geometry and Modelling

INFORMATION NOTICE ON COOKIES

IIT's website uses the following types of cookies: browsing/session, analytics, functional and third party cookies. Users can choose whether or not to accept the use of cookies and access the website. By clicking on "Further Information", the full information notice on the types of cookies will be displayed and you will be able to choose whether or not to accept them whilst browsing on the website
Further Information
Accept and close