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Student assistant (HiWi) as AI Software Engineer for Structural Health Monitoring of real Buildings and Bridges in Zürich

Studierende finden an der ETH Zürich ein Umfeld, das eigenständiges Denken fördert, Forschende ein Klima, das zu Spitzenleistungen inspiriert.

Jobbeschreibung

30%-40%, Zurich, fixed-term

Over 50% of the existing buildings and bridges in Europe have exceeded their design lifespan and do not fulfil current safety standards. Replacing all the obsolete infrastructure comes at an unbearable monetary and environmental cost, as almost 40 % of the global CO2 emissions are already attributed to the construction industry. Recent unexpected bridge collapses exposed the necessity to monitor the structural condition efficiently and reliably. While maintenance today relies on visual inspections, critical damage is not always visible on the surface of structures.

Similar to medical doctors that measure our vital signals to formulate a firm diagnosis, engineers need to monitor the structural condition to provide optimal maintenance solutions. Our vision is to revolutionize the maintenance of buildings and bridges by translating vibrations due to wind or regular operation (traffic) into structural condition metrics, independent from the construction material and without prior knowledge about the type and location of the damage. For this, we combine cutting-edge AI tools with low-cost sensors and we develop an online IoT platform that monitors the "heartbeat" of real buildings and bridges. Our mission is to improve the resilience of our society in response to catastrophes and to minimize the environmental footprint of our buildings and bridges, by extending their safe operational life.

Project background

To tackle these challenges, we assimilate data, obtained from appropriately instrumented buildings and bridges, into the modelling, condition assessment, diagnostics and virtualization of engineered systems. We adopt Structural Health Monitoring methods & tools for evaluating structural integrity, durability and reliability throughout the structural life cycle, as well as for supporting decisions for optimal maintenance planning and safe operation. We are convinced that a proper combination of hardware resources and computational tools can ultimately lead to an intelligent, data-driven infrastructure management system, where diagnosis & prognosis of condition no longer depends merely on sporadic visual inspections.

We are a team of passionate researchers and experienced professionals intending to bridge the gap between research and practice in the most necessary, expensive and environmentally harmful industry: the construction sector. We believe that combining knowledge from different disciplines is the key to providing revolutionary solutions, will you join us?

Job description
  • Explore, deploy and evaluate novel AI tools for damage detection and characterization on benchmark vibrational data (time-series) from real structures.
  • Integrate the developed processing routines in a broader framework for permanent monitoring applications.
  • Support the development of the front-end for the visualization of the computed damage metrics.
Your profile
  • You are a matriculated student at ETH with background and interest in applied Machine Learning for time-series data.
  • You hold experience in front-end development, ideally with time-series data applications.
  • You are interested in applied AI and you are excited to work on an innovative, practical and high-impact project.
  • You are responsible and able to work independently on your tasks.
  • You are not occupied with other employment contracts (even HiWi positions) during the Fall semester 2022.
Your workplace
We offer

We offer a student assistant position (HiWi), contributing to a high-impact practical project, for the Fall semester 2022, with an option for extension. The maximum occupation during the semester is 15 hours/week, which could be extended during semester holidays. We support home office and provide exciting opportunities to participate in field monitoring campaigns.

We value diversity
In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our to find out how we ensure a fair and open environment that allows everyone to grow and flourish.

Veröffentlicht am

30-10-2022

Extra Informationen

Status
Inaktiv
Standort
Zürich
Jobart
Werkstudentenstelle
Tätigkeitsbereich
Technik / Elektronik
Führerschein erforderlich?
Nein
Auto erforderlich?
Nein
Motivationsschreiben erforderlich?
Nein

Zürich | Technik Stellenangebote | Werkstudentenstelle

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