Project Engineer in AI-Based Condition Monitoring

Join a Leading Competence Center in Switzerland

At inspire AG, a strategic partner of ETH Zurich, we excel in product innovation and advanced manufacturing. Our mission is to translate academic research into practical applications in the mechanical, electrical, and metal industries.

Project Overview

We are looking for a dedicated engineer to contribute to a funded innovation initiative with a Swiss industrial collaborator. This project emphasizes sensor-based and model-based approaches for real-time condition assessment and predictive maintenance of safety-critical mechanical systems, utilizing a blend of multisensor data, AI methods, physical models, experiments, and industrial validation.

Key Responsibilities

• Develop hybrid physical and data-driven models for condition assessment and lifetime prediction.
• Design and validate AI methodologies to identify degradation patterns in multisensor data.
• Create comprehensive pipelines for data acquisition, preprocessing, synchronization, annotation, and model training.
• Construct and validate sensor-based laboratory test environments and conduct experimental investigations.
• Implement validation of developed methods within an industrial context.

Ideal Candidate Profile

Experience Requirements

• CH/EU/EFTA citizenship or a valid Swiss work permit.
• Master's degree from ETH or a university in mechanical engineering, mechatronics, robotics, computer science, or a comparable field.
• Background in machine learning, computer vision, signal processing, or condition monitoring.
• Proficiency in Python programming and experience with experimental data.
• A strong interest in integrating mechanical modeling, experiments, and AI for safety-critical industrial systems.

Interpersonal Skills

• Self-motivated, organized, and keen to explore innovative technologies.
• Analytical mindset with effective problem-solving abilities.
• Adept in interdisciplinary, industry-focused teamwork.
• Fluency in both German and English.

Work Environment

This role presents a distinctive opportunity to engage at the crossroads of AI, sensor technology, mechanical modeling, and industrial experimentation. You will devise and validate cutting-edge condition-monitoring methodologies, transitioning from laboratory experiments and modeling to real-world applications. The position offers a blend of academic rigor and practical engineering experience, with ample opportunities for growth in applied research and development.

Engage with Us

We invite you to connect with our innovative team and explore what we can achieve together.