positions

Task: Zero-power network pervasive intelligence (WP2)

Host institution: UNITN

Country: Italy

Supervisor: Prof. K. Yildirim [UNITN]

Co-supervisors: Prof. O. Saukh [TU Graz]; Dr. B. Guzman [SFI]

Objectives: 1) To enable zero-power and battery-less pervasive networked intelligence by novel protocols and scheduling algorithms; 2) To design networked inference model; 3) To validate the proposed solution.

Expected Results: Self and continual learning pipeline and distributed inference algorithms; 2) New energy-centric communication and synchronisation protocols; 3) A proof-of-concept zero-power network demonstration that supports networked intelligence.

PhD enrolment: Doctoral School of UNITN

Planned secondments: 

• TU Graz (3 months, M16-M18): Energy-efficient self and continual learning algorithms, with Prof. O. Saukh (KPI: joint conference paper)

• SFI (4 months, M28-M31): Proof-of-concept zero-power networked intelligence for smart farming, with Dr. B. Guzman (KPI: joint conference paper)

Candidate profile: computer science, electronics engineering, information engineering, telecommunications engineering, or equivalent discipline

Desirable skills/interests: embedded systems, machine learning, low-power wireless networking, good programming skills (C/C++/Assembly Language)

Application Deadline: February 14, 2025, AoE

Descriptions of all the 18 DC Positions

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