PhD position in Smart Sensors & Energy Efficient Machine Learning

In this role, you will benefit from advanced training in various European universities and industry, participate in scientific discussions within the rich context of the Marie Skłodowska-Curie Action Doctoral Network (MSCA DN) DIAMOND.

Doctoral candidate position A-DC2 will be hosted and matriculated at ETH Zurich, with planned secondments at STMicroelectronics (Itay) and the University College Dublin. The doctoral candidate will work on designing novel Smart Sensors & Energy Efficient Machine Learning on Microcontrollers.

The objectives of this thesis include:

• Design and prototype modular, low-cost sensor nodes integrating vibration, strain, and environmental sensors with MCU-class edge AI capabilities. Optimize sensing front-ends, power management, and communication interfaces for minimal standby and inference energy.
• On-chip AI and signal preprocessing: Implement on-node feature extraction (FFT, modal parameters, transmissibility metrics) and deploy quantized TinyML models co-developed with ADC1. Enable adaptive sensing and duty-cycling strategies responsive to structural dynamics.
• Energy harvesting and lifetime optimization. Integrate multi-source energy harvesting (vibration, solar, RF, etc.) and dynamic power management policies to achieve energy neutrality and autonomous operation in long-term deployments.
• Edge–cloud integration and field deployment. Deploy and validate sensor networks on representative assets (bridge testbeds, turbine rigs), interfacing seamlessly with ADC1’s graph analytics and hybrid digital twins. Quantify energy, latency, and data-rate improvements against cloud-based baselines.

This position is offered for 36 months, with the earliest starting date as agreed upon recruitment. The primary academic advisor is PD. Dr Michele Magno (ETH Zurich, D-ITET), under close collaboration with Prof. Eleni Chatzi (ETH Zurich, D-BAUG, supervisor of A-DC1), and additional mentorship provided during secondments.

Applicants must hold a:

• M.Sc. Diploma (120 ECTS points) or equivalent in civil, mechanical or electrical engineering, geosciences, physics, applied mathematics, computer sciences or related fields, and be at the beginning of their research career.
• Principal qualifications include strong analytical and quantitative skills in numerical analysis, programming, high-performance computing, as well as skills in dynamics & structural health monitoring, data analysis and modelling, and interest in laboratory-based experimentation and engineering applications.
• A solid knowledge of English as the spoken and written language of work is mandatory.

We expect good interpersonal skills, the ability to thrive in a diverse, multidisciplinary environment, ability to present work in international conference, as well as the willingness to spend a number of months working with project collaborators at partner universities in this project.

Eligibility Criteria: Researchers can be of any nationality. At the time of recruitment, researchers:

• Should not have been awarded a title of PhD (Applicants who have successfully defended their doctoral thesis but not yet formally been awarded the doctoral degree will not be considered eligible.)
• Should not have resided or carried out your main activity in Switzerland, for more than 12 months within the last 3 years