Bridge Monitoring & Vision: Student Research Assistant

ETH Zurich; Zürich; On-site; CHF 34,000 - 48,000; Part time

Benefits offered by this job

Salary according to ETH Zurich rates

Access to HPC resources

On-site workplace at Hönggerberg

Hands-on bridge monitoring experience

Supervision by international team

Collaborative research environment

Job summary

ETH Zurich’s Chair of Structural Mechanics & Monitoring in Zurich seeks a motivated Student Research Assistant to support the SwissBWIM project. The role focuses on bridge load identification and condition assessment using multi-modal data and advanced computer vision techniques.

You will work on data preprocessing, traffic video analysis, and integrating vehicle trajectories with bridge responses to assess structural behavior and performance.

Qualifications

• Enrolled at a university in Zurich or the nearby area.
• Background in civil/structural engineering, mechanical engineering, data science, computer science, or related fields.
• Experience or strong interest in two or more areas: bridge engineering, structural dynamics, sensing systems, data analysis and machine learning, or computer vision (object detection, tracking, localization).
• Familiar with Python programming. MATLAB and Linux are advantages.
• Can dedicate 15 hours per week to the project.
• Proficient in English; working language is English.

Responsibilities

• Multi-modal data preprocessing: synchronising measurements and cleaning faulty data.
• Traffic video analysis: deep-learning-based vehicle detection and tracking; data labelling; model fine-tuning.

Skills

Structural engineering

Signal processing

Data science

Computer vision

Python

MATLAB

Linux

Tools

Python

MATLAB

Linux

Job description

ETH Zurich’s Chair of Structural Mechanics & Monitoring in Zurich seeks a motivated Student Research Assistant to support the SwissBWIM project. The role focuses on bridge load identification and condition assessment using multi-modal data and advanced computer vision techniques.

You will work on data preprocessing, traffic video analysis, and integrating vehicle trajectories with bridge responses to assess structural behavior and performance.