The Chair of Structural Mechanics and Monitoring at ETH Zurich invites applications for a fully funded PhD position in Data-Informed Reduced Order Modelling for Wind Energy Structures, as part of the Marie Skłodowska-Curie Doctoral Networks (MSCA-DN) project COMBINE. This international doctoral network brings together leading academic and industrial partners to address advanced modelling, simulation, sensing, and data analysis challenges in engineering systems, with a focus on decarbonization and sustainable energy solutions. The COMBINE-DC17 position is hosted at ETH Zurich, Switzerland, and centers on developing adaptive reduced order model (ROM) frameworks for coupled problems in wind energy structures. The research aims to advance ROM methodologies for fluid–structure interaction (FSI) and real-time monitoring/control in wind turbine systems. Key objectives include integrating real-time monitoring data and virtual sensing to dynamically select and adjust model fidelity, designing and validating virtual sensing methods, implementing ROMs for FSI in wind turbines, and demonstrating adaptive ROMs for real-time simulation, decision support, and control in offshore wind energy contexts. As a doctoral candidate, you will benefit from network-wide training activities, interdisciplinary collaborations, and planned secondments to partner institutions (UGENT, TUM, CIMNE). The position offers a vibrant international research environment, structured doctoral training, and opportunities for industry and academic visits within the consortium. Upon completion, you will gain a comprehensive understanding of the research-to-innovation process and build a strong international network. Applicants must hold an M.Sc. or equivalent in civil, mechanical, or electrical engineering, geosciences, physics, applied mathematics, computer sciences, or related fields. Essential qualifications include strong analytical and quantitative skills in numerical analysis, programming, high-performance computing, dynamics and structural health monitoring, data analysis and modelling, and interest in laboratory-based experimentation. Proficiency in English is required, along with good interpersonal skills, ability to work in a multidisciplinary environment, and willingness to spend time at partner universities. Eligibility criteria: 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 in the last 3 years. ETH Zurich is renowned for its excellence in science and technology, offering a diverse and inclusive environment that values equality, sustainability, and independent thinking. The university provides a climate-neutral future vision and supports the rights and dignity of all staff and students. Applications are accepted exclusively through the ETH Zurich online portal. Required documents include a letter of motivation, CV, clear designation for the position COMBINE DC17, academic diplomas and certificates, and contact details for two referees. The review process begins January 15th 2026 and concludes by April 30th 2026. For further information, visit the Chair of Structural Mechanics and Monitoring website at ETH Zurich.

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.

This PhD position at ETH Zurich, hosted within the Met2Adapt (M2A) European Training Network, focuses on the development of active meta-structures for enhanced damage detection and localization on wind turbine blades. The project is part of a large, multi-institutional initiative funded by the European Commission’s Horizon 2020 Marie Skłodowska-Curie programme, aiming to deliver sustainable meta-materials and intelligent meta-components for the renewable energy sector. As ESR16, the doctoral candidate will address the complex problem of detecting and localizing damage in wind turbine blades, which are subject to challenging mechanical and environmental loads throughout their lifecycle. The research objectives include classifying damage topologies on blades, designing surface-bonded metamaterials as meta-filters for guided waves, and performing both numerical and experimental validation on laboratory and real-world blades. The project integrates advanced computational solid mechanics, nonlinear dynamics, data analysis, and mechatronics, with a strong emphasis on experimental work and engineering applications. The position is supervised by Professor Eleni Chatzi (ETH Zurich), with co-advisors Dr. Vasileios Ntertimanis (ETH Zurich) and Dr. Andrea Colombi (Zurich University of Applied Sciences, ZHAW). The successful candidate will join a vibrant, multidisciplinary network spanning nine countries, offering opportunities for collaboration, industry visits, and skill development across academia and the renewable energy sector. Eligibility requirements include a master’s degree (or equivalent) in civil, mechanical, or electrical engineering, geosciences, physics, applied mathematics, or related fields. Candidates must be in the early stages of their research career, possess strong analytical and quantitative skills, and demonstrate proficiency in English. Additional requirements include compliance with ETN mobility rules (not having resided in Switzerland for more than 12 months in the last three years, and not holding a doctoral degree), as well as interpersonal skills and willingness to work at partner institutions. The position offers a 36-month contract with a competitive stipend and mobility allowance, as well as access to a broad network of academic and industry partners. ETH Zurich provides an inclusive, diverse, and sustainability-focused environment, supporting personal and professional growth. Applications are accepted exclusively through the ETH Zurich online portal, with review beginning February 1, 2026 and concluding by April 30, 2026. Required documents include a motivation letter, CV, designation of M2A ESR16, academic diplomas and certificates, and referee contact details (with at least one reference letter uploaded). For further information, candidates may contact Dr. Vasileios Ntertimanis at [email protected]. More details about the Chair of Structural Mechanics and Monitoring at ETH Zurich are available on their website. ETH Zurich is recognized globally for excellence in science and technology, fostering independent thinking and solutions for global challenges.

ETH Zürich invites applications for a PhD position in Meta-Structures with Autonomous Sensing Capacities, as part of the Met2Adapt (M2A) European Training Network funded by the Horizon 2020 Marie Skłodowska-Curie programme. This position (ESR15) is one of 16 doctoral opportunities across Europe, focusing on the development of sustainable meta-materials for vibration mitigation, self-aware meta-components, and carbon-efficient meta-structures for the renewable energy sector. The research will center on engineering novel meta-material architectures with optimal vibration mitigation capabilities, tailored to mechanical and environmental stimuli relevant to wind and wave energy production. The project aims to innovate multi-physics simulation frameworks, design self-tuned and resilient meta-structures, and deliver closed systems empowered with intelligent structural health monitoring (SHM) and prognostics capabilities. ESR15 at ETH Zurich will specifically develop metamaterials-based structures and devices that harvest vibration energy to power sensors and enable data communication. This involves designing metamaterials to guide and amplify vibrations, maximizing energy harvesting and sensing through autonomous adaptation using embedded actuation systems. The doctoral position is offered for 36 months, with the earliest start date as agreed upon recruitment. The primary advisor is Professor Eleni Chatzi (ETH Zurich, DBAUG), with co-advisors Dr. Andrea Colombi (Zurich University of Applied Sciences, ZHAW) and Dr. Vasileios Ntertimanis (ETH Zurich). The successful candidate will join a vibrant, multidisciplinary consortium spanning nine countries, with opportunities to collaborate with industry and academic partners. Applicants must hold a M.Sc. Diploma (120 ECTS points) or equivalent in civil, mechanical or electrical engineering, geosciences, physics, applied mathematics, or related fields, and be at the beginning of their research career. Required skills include strong analytical and quantitative abilities in computational solid mechanics, nonlinear dynamics, data analysis, mechatronics, and laboratory-based experimentation. Proficiency in English is essential. Candidates must not have resided or carried out their main activity in Switzerland for more than 12 months within the last 3 years, must be in the first four years of their research careers, and must not yet have a doctoral degree. Good interpersonal skills, the ability to present work at international conferences, and willingness to spend months at partner universities are expected. ETH Zurich offers a diverse and inclusive environment, promoting equality of opportunity and sustainability. The M2A network provides extensive training, industry visits, and a strong career-defining network. Funding is provided through the Marie Skłodowska-Curie programme, including a stipend and mobility allowance for the duration of the contract. Applications should be submitted online via the ETH Zurich portal, including a letter of motivation, CV, clear designation of M2A ESR15, electronic copies of academic diplomas and certificates, and contact details for at least two referees (with at least one uploaded reference letter). Applications will be reviewed starting February 1, 2026, with the search concluding by April 30, 2026. For further information, visit the Chair of Structural Mechanics and Monitoring at ETH Zurich or contact Dr. Vasileios Ntertimanis at [email protected]. Please note that only online applications will be considered. ETH Zurich is a world-leading university specializing in science and technology, renowned for its excellent education, cutting-edge research, and commitment to sustainability and diversity. Join us to contribute to innovative solutions for global challenges in renewable energy and advanced materials.

ETH Zürich invites applications for a PhD position in Decision Support at the Fleet Level, hosted within the Marie Skłodowska-Curie Action Doctoral Network (MSCA DN) DIAMOND. This position is part of a pan-European initiative 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 join a vibrant research network spanning leading academic institutions and industrial partners across Europe, with the opportunity for advanced training and secondments at Rambøll and CEA. The research focus is on developing next-generation distributed intelligence and decision support systems for fleet-level monitoring. Key objectives include the creation of graph-based and stochastic models for decentralized condition assessment and predictive maintenance, as well as the integration of smart sensing, uncertainty quantification, and asset typologies into scalable, real-time decision-support modules. The project offers a unique multidisciplinary environment, combining civil, mechanical, and electrical engineering with computer science and applied mathematics. Supervision will be provided by Prof. Eleni Chatzi (ETH Zurich, D-BAUG), with close collaboration from Dr. Michele Magno (ETH Zurich, D-ITET) and additional mentorship during secondments. The position is fully funded for 36 months under the MSCA DN DIAMOND program, including a competitive stipend, training opportunities, and industry exposure. The candidate will benefit from a strong career-defining network and gain expertise from research through innovation to industry implementation. Applicants must hold a M.Sc. Diploma (120 ECTS points) or equivalent in relevant fields and be at the beginning of their research career. Required skills include numerical analysis, programming, high-performance computing, structural health monitoring, data analysis, and modelling, with a solid command of English. Candidates should demonstrate strong interpersonal skills, thrive in a multidisciplinary setting, and be willing to spend time at partner institutions. Eligibility criteria include not having been awarded a PhD and not having resided or carried out main activity in Switzerland for more than 12 months in the last 3 years. ETH Zürich is committed to diversity, sustainability, and equal opportunity, fostering an inclusive environment for all staff and students. Applications are accepted exclusively via the ETH Zurich online portal, with review starting January 15th, 2026 and closing April 30th, 2026. Required documents include a letter of motivation, CV, designation for DIAMOND A-DC1, academic diplomas and certificates, and contact details for two referees. For further information, visit the Chair of Structural Mechanics and Monitoring at ETH Zurich or contact Prof. E. Chatzi at [email protected] (questions only). Join ETH Zürich and the DIAMOND network to contribute to cutting-edge research in infrastructure monitoring and decision support, and develop skills for a broad landscape of future opportunities.