Ph.D. OPPORTUNITIES @ IPLAB - University of Catania

We are seeking for two exceptional and passionate full-time Ph.D. students to work on two R&D projects jointly supervised by the University of Catania (Sicily, IT) and two involved partners (see all the details below).

The Image Processing Laboratory (IPLab) is part of the department of Mathematics and Computer Science of the University of Catania, Italy. IPLAB’s research focuses in the areas of Image Processing, Computer Vision, Machine Learning and Computer Graphics. IPLAB has been involved in different international projects for the development of advanced algorithms with applications in different domains: Embedded and wearable devices, assistive technologies, quality of life, forensics, medical, cultural heritage.

The student will have the possibility to work in a friendly and constructive environment and will have the possibility to attend at the major conferences and schools in the field to present the results of his/her research. Equal opportunities to all applicants will be provided.

Any expertise or prior knowledge in computer vision, machine learning and image processing is welcome. Prior publication at international conferences is an advantage. Ability to program in Matlab/Phython/C/C++ is desirable. Other programming languages, communication skills and team play will also be welcome.

If you know any good candidates, please feel free to forward this email. Ask them to send CV, a cover letter, the publication list (if any) to Prof Sebastiano Battiato ( and Dr. Giovanni Maria Farinella (

Application Deadline: 6 Sept 2016

PhD Position A

Ambient Assisted Living with focus on Fall Detection
University of Catania – IPLAB (Catania, Italy) & OSRAM (Munich,DE)

Academic Supervisor:
Dr. Giovanni Maria Farinella:

Brief Description
The main aim of this PhD. programme is the design and development of a low-cost and noninvasive Fall Detection System based on visual data acquired with fish-eye cameras mounted on the roof of a room (e.g., in a roof-lamp). Attention will be taken in the development of a solution able to work in embedded systems with weak supervision for training (offline) and/or automatic training after the installation (online). The Fall Detection solution will be designed and developed by keeping in mind indoor environments such as Homes, Hospital Rooms and Nursing Homes & Clinics.

PhD Position B

Learning Architectures for Multimedia Representation and Understanding
University of Catania – IPLAB (Catania, Italy) & STMICROELECTRONICS (Catania, Italy)

Academic supervisor:
Prof Sebastiano Battiato:

Brief Description
The aim of this Ph.D. programme is to use data coming from different domains (images, video/temporal/motion, GPS, audio signals, tags, wearable sensors, etc.) to build a powerful representation, possibly extending the current CNN to treat the different signal jointly and in a semi-supervised way (i.e., with no need of huge datasets to perform training for personalized use). The application contexts will consider emerging scenarios, such as activity monitoring and assistive technologies to improving health and wellness of human beings and quality of life in general.