<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
</head>
<body style="overflow-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;">
<div>We are seeking <b>two</b> highly motivated researchers for fully funded research fellowship positions (Italian Assegno di Ricerca – Post-Doc Equivalent) on topics related to Object Tracking in Egocentric Vision.</div>
<div> </div>
<div>The candidate will join the Machine Learning and Perception Lab (MLP Lab), at the University of Udine, Italy under the supervision of Prof. Christian Micheloni and Dr. Matteo Dunnhofer.</div>
<div> </div>
<div>The two positions are in topics related to two recently funded projects: EXTRA-EYE and TEAM, with specific focus on developing object tracking algorithms for first-person egocentric videos. More details on the two open positions are in the following:</div>
<div> </div>
<div><b>Position 1 - Design and Development of Object Tracking Algorithms for localisation across First-Person and Third-Person Views</b></div>
<div><u>Position:</u> Research Fellow (post-doc equivalent)</div>
<div><u>Location: </u>University of Udine, Udine, Italy</div>
<div><u>Application Deadline:</u> January 12, 2024 at 2:00 pm (Italian time)</div>
<div><u>Link to the Call (with instructions on how to apply):</u> <a href="https://titulus-uniud.cineca.it/albo/viewer?view=files/002449312-UNUD001-152cbef6-7f6d-4954-a746-7d67bceac137-002.pdf">https://titulus-uniud.cineca.it/albo/viewer?view=files/002449312-UNUD001-152cbef6-7f6d-4954-a746-7d67bceac137-002.pdf</a></div>
<div><u>Duration:</u> 18 Months</div>
<div><u>Research Topics:</u> Tracking objects in first-person view is notoriously challenging, and EXTRA-EYE aims to pioneer a solution. Our approach involves integrating state-of-the-art deep learning architectures for third-person-view (TPV) tracking with
first-person-view (FPV) specific cues, such as the position of the user's hands. The project will establish correspondences between scenes captured in the FPV and TPV streams, creating a holistic, robust, and efficient tracking approach capable of real-time
tracking across multiple dynamic and static cameras. </div>
<div><u>Link to the project’s website:</u> <a href="https://sites.google.com/view/extraeye/home">https://sites.google.com/view/extraeye/home</a></div>
<div> </div>
<div><b>Position 2 - Design and Development of Long-Term Object Tracking Algorithms for Episodic Memory Tasks</b></div>
<div><u>Position:</u> Research Fellow (post-doc equivalent)</div>
<div><u>Location:</u> University of Udine, Udine, Italy</div>
<div><u>Application Deadline:</u> January 30, 2024 at 2:00 pm (Italian time)</div>
<div><u>Link to the Call (with instructions on how to apply):</u> <a href="https://titulus-uniud.cineca.it/albo/viewer?view=files/002464259-UNUD001-a253fd01-2407-4257-bcc9-c8feaa039e8e-002.pdf">https://titulus-uniud.cineca.it/albo/viewer?view=files/002464259-UNUD001-a253fd01-2407-4257-bcc9-c8feaa039e8e-002.pdf</a></div>
<div><u>Duration:</u> 18 Months</div>
<div><u>Research Topics:</u> The research activity will focus on long-term tracking of previously detected objects, exploiting first-person vision cues and merging single with multiple object tracking methodologies to efficiently locate and monitor several
objects of interest. The research will be carried within the framework of the PRIN PNRR 2022 "TEAM" project, with close collaboration with partner institutions to achieve the project's objectives.</div>
<div><u>Link to the project’s website</u>: <a href="https://sites.google.com/view/prin-pnrr-team">https://sites.google.com/view/prin-pnrr-team</a></div>
<div> </div>
<div><b>Admission Criteria</b></div>
<div>To participate in the call, a master’s degree in computer science or computer science engineering is required. A PhD is not required, but strongly recommended. Previous background in Computer Vision and Deep Learning is also strongly recommended.</div>
<div><b> </b></div>
<div><b>About the Laboratory</b></div>
<div>The MLP research group mainly focuses on the development of research in Computer Vision and Deep Learning for Object Tracking and Re-Identification, and Distributed Camera Systems. The group has 6+ members.</div>
<div> </div>
<div>The MLP group has a track record of previous publications in prestigious venues (CVPR, ICCV, ECCV, TPAMI, IJCV, …) and several research projects on both fundamental and application-oriented research, in collaboration with several industrial and academic
partners. </div>
<div> </div>
<div>The group aims to provide its members a friendly environment with strong supervision, in which individuals can grow and let their full potential flourish. We regularly organize group meetings and gatherings outside the lab to keep the team motivated and
encourage a good work culture.</div>
<div> </div>
<div> </div>
<div>Please feel free to share this opportunity with anyone who might be interested. We appreciate your assistance in reaching out to potential candidates.</div>
<div> </div>
<div>Christian Micheloni, University of Udine</div>
<div>Matteo Dunnhofer, University of Udine</div>
</body>
</html>