Key responsibilities

The work model for the role is: #LI-Hybrid

You will be mainly accountable for:

• Contributing to ongoing research activities on analytics and condition monitoring of electromechanical signals, helping us develop algorithms for detecting electrical and mechanical degradation.
• Analyzing sensor data from industrial systems and developing model-based and data-driven algorithms for detecting failure and degradation.
• Setting up a data pipeline for managing large amounts of data and visualizing results clearly and effectively.
• Investigating machine learning techniques alongside physics-based modeling.
• Taking ownership of independent tasks as part of the project team.
• We expect you to show readiness to tackle difficult problems, strong motivation to implement and test models and algorithms, and a proactive attitude toward generating new ideas to overcome challenges.

Qualifications for the role

• You are a Master’s student in Computer Science, Electrical Engineering, Mathematics, Physics or a related field.
• You have experience with data analysis and signal processing methods such as advanced FFT techniques, wavelets, order analysis, outlier detection, etc.
• You have advanced programming skills in MATLAB.
• You have experience with mechanical signals and vibration measurements and / or electrical systems.
• You are fluent in English.
• You are interested in learning about condition monitoring for industrial systems.
• You have strong analytical skills and a proactive mindset.
• You are motivated, friendly, and capable of working independently.
• You demonstrate team spirit, openness, and initiative.

Interested in joining our team? We are looking forward to receiving your complete application (CV, Cover letter, Transcript of records) through our online tool. In the case of equal suitability, people with severe disabilities and their equals are given preference.

ABB AG

+49 (0) 621 381 3500

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