New Internship opportunities @ CYENS CoE

 

We are excited to announce that CYENS Centre of Excellence is offering a range of exciting internship opportunities (both paid and unpaid) for students eager to gain valuable hands-on experience in various fields. We would appreciate if you could share these with your network.

For more information about our internship opportunities and how to apply, please visit our website https://www.cyens.org.cy/en-gb/vacancies/placement-opportunities/internships/.

 

  1. Research Internships 2024 (paid)
  2. Accounting & Finance Internship
  3. Graphic Designer Internship
  4. Marketing Internship
  5. Procurement Internship
  6. iNicosia Digital Twin | Architecture, Architectural Engineering, Civil Engineering, and Geomatics Internship
  7. iNicosia Digital Twin | Unity and/or Unreal Engine Engineer Internship
  8. Thinker Maker Space (Paid Internship)
  9. HR Internship

 

Thank you for your continued support in helping us foster the next generation of talent.

 

Best regards,

 

Natasa Kafkalia
HR Officer, Assoc CIPD

 

T. +357 22747575
www.cyens.org.cy

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Free Webinar by Dr. Xiaoming Liu on “Biometric Recognition in the Era of AI Generated Content (AIGC)”

The IEEE Biometrics Council invites participants to the upcoming (free)
webinar by Prof. Xiaoming Liu on “Biometric Recognition in the Era of AI
Generated Content (AIGC)”. Detail on the webinar are given below:

Title: Biometric Recognition in the Era of AI Generated Content (AIGC)
Speaker: Prof. Xiaoming Liu, Michigan State University, USA
When: 24 April 2024, at 10am EST (4pm CEST, 7am PST, 10pm Beijing Time)
Where: Online (Zoom)
Registration: (free, but required):
https://us06web.zoom.us/webinar/register/WN_S_9bjNaOTMGVvD55MYAcVg

*** Talk Summary ***
In recent years we have witnessed impressive progress on AIGC
(Artificial Intelligence Generated Content). AIGC has many applications
in our society, as well as benefits diverse computer vision tasks. In
the context of biometric recognition, we believe that the AIGC era calls
for innovation on both data generation and how to leverage the generated
data. In this talk, I will present a number of efforts that showcases
these innovations, including: 1) how to bridge the gap between the
training data distribution and test data distribution; 2) how to
generate a complete synthetic database to train face recognition models;
3) how to estimate the 3D body shape from an image of clothed human
body; and 4) how to manipulate a human body image by changing its body
pose, clothing style, background, and identity. In the end, we will
briefly overview other research efforts in the Computer Vision Lab at
Michigan State University.

*** About the Speaker ***
Dr. Xiaoming Liu is the MSU Foundation Professor, and Anil and Nandita
Jain Endowed Professor at the Department of Computer Science and
Engineering of Michigan State University (MSU). He is also a visiting
scientist at Google Research. He received Ph.D. degree from Carnegie
Mellon University in 2004. Before joining MSU in 2012, he was a research
scientist at General Electric Global Research. He works on computer
vision, machine learning, and biometrics, especially on face related
analysis and 3D vision. Since 2012, he helps to develop a strong
computer vision area in MSU, who is ranked top 15 in US according to
csrankings.org. He is an Associate Editor of IEEE Transactions on
Pattern Analysis and Machine Intelligence. He has authored more than 200
publications and has filed 35 patents. His work has been cited over
25000 times with an H-index of 76. He is a fellow of IEEE and IAPR.

For more information, visit:
https://ieee-biometrics.org/index.php/activities/webinars

AIIA/AIDA/TEMA Summer School: “CVML Programming Short Course and Workshop on Deep Learning, Computer Vision and Big Data Analytics 2024”, 27-29 August 2024, Thessaloniki, Greece.

Dear AI/CS/ECE student/scientist/engineer/enthusiast,

the Artificial Intelligence and Information Analysis (AIIA) Lab of Aristotle University of Thessaloniki (AUTH) in cooperation with (TEMA) R&D project, the International AI Doctoral Academy (AIDA), is excited to invite you to register and attend the upcoming “CVML Programming Short Course and Workshop on Deep Learning, Computer Vision and Big Data Analytics 2024” which will take place in Thessaloniki, Greece from August 27th to 29th 2024.

This Summer School offers a three-day short course that delivers an in-depth exploration of programming tools and techniques for addressing a variety of computer vision and deep learning challenges. The course focuses on the fundamentals of deep learning and its applications in Natural Disaster Management. Here's a glimpse of what the course entails:

  • Deep neural networks – Convolutional NNs
  • 2D Object Tracking in Embedded Systems
  • Real Time Object Detection.
  • Real-Time Image Segmentation.
  • Natural Language Processing.
  • Explainability in Computer Vision applications.

Additionally, hands-on programming workshops will be conducted on each topic, providing participants with practical experience and skills enhancement.

Details

Host Institution: Aristotle University of Thessaloniki

27, 28, 29 August 2024, 08:30- 16:30 EEST (UTC + 3 hours)

On-site Participation: KEDEA Building, AUTH, Thessaloniki, Greece

General Registration

Early registration (till 15/07/2024)

Students/Scientists, Engineers from other scientific disciplines having the necessary mathematical background are also welcomed to register.

 

Special Registration for AIDA Students*

 

 On top of the above registration, also enroll on this course using the “ENROLL ON THIS COURSE” button on the AIDA course page, so that this course is included on your AIDA Certificate of Course Attendance upon successful completion of the program.

 

*AIDA Students are PhD students/candidates or Postdoc researchers belonging to any AIDA member.

 

Upon successful completion of the course, participants will receive a certificate of attendance issued by Aristotle University of Thessaloniki.

For more details, please visit: https://icarus.csd.auth.gr/cvml-programming-short-course-and-workshop-on-deep-learning-computer-vision-and-big-data-analytics-2024/

 

This summer school is technically sponsored by TEMA , AI.BIG Cluster, AIDA, AI4Media R&D projects.

 

 

School Organizer: Prof. Ioannis Pitas

Chair of the International AI Doctoral Academy (AIDA), Director of the Artificial Intelligence and Information analysis (AIIA) Lab,

Aristotle University of Thessaloniki, Greece

Workshop on Recent Advances in Biometrics and its Applications | 2024 47th International Conference on Telecommunications and Signal Processing

Call for papers – Workshop on “Recent Advances in Biometrics and its Applications”, in the 47th International Conference on Telecommunications and Signal Processing (TSP)

July 10-12, 2024 (Virtual Conference, https://tsp.vutbr.cz/ )

https://tsp.vutbr.cz/8th-workshop-biometrics/

Deadline : May 6, 2024

University of Udine, Italy Months Research Fellow Position – Object Tracking in First-Person and Third-Person Videos

Dear colleagues,
We are seeking one highly motivated researcher for a fully funded research fellowship position (Italian Assegno di Ricerca – Post-Doc Equivalent) on topics related to Object Tracking in Egocentric Vision.
 
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.
 
The position is in topics related to a recently funded PRIN project: EXTRA-EYE, with specific focus on developing object tracking algorithms for first-person egocentric and third-person videos. More details are in the following:
 
Position – Design and Development of Object Tracking Algorithms for localisation across First-Person and Third-Person Views
Position: Research Fellow (post-doc equivalent)
Location: University of Udine, Udine, Italy
Application Deadline: May 28, 2024 at 2:00 pm (Italian time)
Duration: 14 Months
Research Topics: 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. 
Link to the project’s website: https://sites.google.com/view/extraeye/home
  
Admission Criteria
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.
 
About the Laboratory
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.
 
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. 
 
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.
  
 
Please feel free to share this opportunity with anyone who might be interested. We appreciate your assistance in reaching out to potential candidates.
 
Christian Micheloni, University of Udine
Matteo Dunnhofer, University of Udine

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