ETH Zürich invites applications for a PhD position in Smart Sensors & Energy Efficient Machine Learning as part of the Marie Skłodowska-Curie Action Doctoral Network (MSCA DN) DIAMOND. This network brings together leading academic institutions and industrial partners across Europe to advance decentralized, data-driven frameworks for robust monitoring and condition assessment of large fleets of civil infrastructure assets, such as bridges, railways, and wind turbines.

The successful candidate will be hosted at ETH Zurich and will benefit from advanced training at various European universities and industry partners, including planned secondments at STMicroelectronics (Italy) and University College Dublin. The research will focus on designing and prototyping modular, low-cost sensor nodes that integrate vibration, strain, and environmental sensors with microcontroller-class edge AI capabilities. Key objectives include optimizing sensing front-ends, power management, and communication interfaces for minimal energy consumption, implementing on-node feature extraction and deploying quantized TinyML models, enabling adaptive sensing strategies, and integrating multi-source energy harvesting for autonomous long-term operation.

The project also involves deploying and validating sensor networks on representative infrastructure assets, interfacing with advanced graph analytics and hybrid digital twins, and quantifying improvements in energy, latency, and data rates compared to cloud-based solutions. The position is offered for 36 months and provides a unique opportunity to collaborate with experts across Europe, gain exposure to both academic and industrial environments, and develop a strong professional network.

Applicants must hold an M.Sc. 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. Required qualifications include strong analytical and quantitative skills in numerical analysis, programming, high-performance computing, dynamics and structural health monitoring, data analysis and modelling, and an interest in laboratory-based experimentation. Proficiency in English is mandatory, along with good interpersonal skills and the ability to work in a multidisciplinary environment. Candidates must not have been awarded a PhD and must not have resided or carried out their main activity in Switzerland for more than 12 months within the last 3 years.

ETH Zurich values diversity, sustainability, and an inclusive culture, offering a supportive environment for personal and professional growth. The DIAMOND program provides funding for 36 months, including a stipend and opportunities for training and secondments. Applications are accepted exclusively through the ETH Zurich online portal, with review beginning January 15th, 2026 and closing April 30th, 2026. Required documents include a letter of motivation, CV, academic diplomas and certificates, and contact details for two referees. For further information, candidates may contact PD Dr. Michele Magno at [email protected].

Join ETH Zurich and the DIAMOND network to contribute to cutting-edge research in smart sensors, energy-efficient machine learning, and infrastructure monitoring, while building a foundation for a successful career in academia or industry.