PhD position in Embedded IoT Intelligence for Battery-free Swimming Milli-robots

Pervasive Wireless Systems Group

Deadline for receipt of applications: February 14th, 2025, 23:59 AoE (15 February 2025, 13:59h Europe/Madrid Time)

IMDEA Networks’ Pervasive Wireless System Group headed by Prof. Domenico Giustiniano invites applications for PhD positions in the framework of HORIZON-MSCA-2023-DN-01-01 ANT Project

Host institution: IMDEA

Country: Spain

Supervisor: Prof. D. Giustiniano [IMDEA]

Co-supervisors: Prof. Q. Wang [TU Delft]; Dr. E. Rocco [A5]

Objectives: 

1) To develop lightweight AI models for extremely energy-constrained swimming milli-robots 

2) To customize the existing hardware design at IMDEA of swimming milli-robots for embedded processing with non-volatile memory and AI intelligence 

3) To test the system on the water and under-water scenarios using in-house battery-free IoT network.

Expected Results:

1) Embedded AI models for processing data of battery-free swimming milli-robots with very-low power sensors 

2) Algorithms for autonomous motion pattern decision of millirobot based on collected data and external inputs 

3) Proof-of-concept evaluation using customized battery-free IoT millirobots.

PhD enrolment: Doctoral School of UC3M

Planned secondments: 

• TU Delft (4 months, M16-M19): Design of embedded AI models for energy-efficient data processing and inference, with Prof. Q. Wang (KPI: joint paper)
• A5 (4 months, M28-M31): Testbed implementation and evaluation of swimming milli-robot in a networked underwater scenario, with Dr. E. Rocco (KPI: joint paper)

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

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

Application Deadline: February 14, 2025, AoE

Submit Your Application HERE

This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No. 101169439.