Work With Us!
We are seeking very motivated candidates in view of the opening of Research Fellow positions to work on this project.
Position Requirements:
A Master's Degree title (PhD preferred).
A strong background in Computer Vision or related fields.
Familiarity with object tracking, egocentric vision, and behavioural analysis.
Ability to work collaboratively within a multi-disciplinary team.
Calls for Application
The calls for application are available at the following links:
Object Tracking from Multiple Views and Memory Forming
Position: Research Fellow (post-doc equivalent)
Admission Criteria: Master’s Degree, but a PhD in Computer Vision is recommended
Location: University of Udine, Udine, Italy
Application Deadline: 30th January 2024, 14.00 (Italian Time)
Link to the Call (with instructions on how to apply): https://titulus-uniud.cineca.it/albo/viewer?view=files/002464259-UNUD001-a253fd01-2407-4257-bcc9-c8feaa039e8e-002.pdf
Duration: 18 Months
Research Topics: The research activity will involve the design of the object tracking module, wich focuses on long-term tracking of detected objects, using first-person vision cues and merging single with multiple object tracking methodologies to efficiently locate and monitor several objects of interest. The researcher will also collaborate with the University of Catania to the development of a memory forming algorithm capable of summarizing information coming from the other modules to tackle the downstream task of episodic memory retrieval.
User-Related Object Discovery and Memory Forming
Position: Research Fellow (post-doc equivalent)
Admission Criteria: Master’s Degree, but a PhD in Computer Vision is recommended
Location: University of Catania, Catania, Italy
Application Deadline: 8th January 2024, 12.00 (Italian Time)
Link to the Call (with instructions on how to apply): https://www.unict.it/sites/default/files/ds_bandi/decreto_n._4953.pdf
Duration: 18 Months
Research Topics: The research activity will involve the design of algorithms for user-object interaction discovery. Such algorithms aim to detect important objects and their interactions, by incorporating information about actions, object categories, and relationships between objects. The researcher will also collaborate with the University of Udine to the development of a memory forming algorithm capable of summarizing information coming from the other modules to tackle the downstream task of episodic memory retrieval.