positions

Task: Distributed inferencing on zero/low power embedded devices in smart farming (WP4)

Host institution: IMDEA

Country: Spain

Supervisor: Prof. D. Giustiniano [IMDEA]

Co-supervisors: Dr. J. Beysens [CSEM]; Dr. F. Widdershoven [NXP]

Objectives: 1) To develop lightweight computation- and memory-efficient embedded AI models on extremely low-battery smart farming sensors; 2) To design distributed inference mechanisms by partitioning the workload across devices within a hierarchical network infrastructure; 3) To design a system and test it through real-life smart farming use cases using battery-free IoT sensors developed by IMDEA.

Expected Results: 1) Embedded AI models suited for battery-free or extremely low-battery smart farming sensors; 2) Distributed inferencing algorithms for hierarchical network infrastructure; 3) Proof-of-concept smart-farming system design & testing using battery-free IoT sensors.

PhD enrolment: Doctoral School of UC3M

Planned secondments: 

• CSEM (3 months, M16-M18): Distributed inferencing algorithms for low-power embedded devices, with Dr. J. Beysens (KPI: joint paper)

• NXP (3 months, M28-M30): Embedded AI models suited for battery-free smart farming sensors, with Dr. F. Widdershoven (KPI: joint paper)

Candidate profile: telecommunication engineering, electrical engineering, computer science (in order of preference)

Desirable skills/interests: signal processing, embedded systems, machine learning(the applicant should be proficient in at least one or two of the skills)

Application Deadline: February 14, 2025, AoE

Descriptions of all the 18 DC Positions

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