Research Assistant in Deep Learning for Complex Engineered Systems 80 - 100%

School: School of Engineering
Starting date: 01.09.2022

Your role

The Smart Maintenance Team of the ZHAW develops solutions for intelligent condition monitoring, fault detection, diagnostics and prognostics of complex technical systems. Our current projects focus on fully automated detection and visualization of anomalies and inefficiencies in renewable energy systems. Our focus is on implementing state-of-the-art research ideas from machine learning and deep learning in real operational systems.

As a member of our research team, you will develop innovative approaches to tackle challenges within applied research projects in close collaboration with our industry partners in the field of condition based and predictive maintenance.

Your tasks will include:

• Developing and implementing data-driven algorithms for detection, diagnostics and prognostics of incipient failures in industrial assets and infrastructures.
• Developing innovative approaches using state of the art statistical, machine learning and deep learning methods.
• Combining engineering knowledge with data science techniques.
• Executing and taking responsibility of R&D activities in collaboration with our industry partners.
• Possibly participating in teaching assistance for statistics courses.

Your profile

• Highly motivated candidate with an MSc or PhD degree in engineering, computer science, statistics, applied mathematics, physics or related field.
• Programming experience in Python. Experience with TensorFlow and Keras/PyTorch is advantageous.
• Experience with applying data analytical and machine learning methods.
• Experience with deep leaning algorithms is advantageous.
• Fluency in English (both written and spoken) and preferably also in German. 

We encourage applications from proactive and self-motivated candidates with analytical thinking and strong problem-solving passion and abilities, good communication skills and original thinking.

This is what we stand for

Zurich University of Applied Sciences ZHAW is one of Switzerland's largest multidisciplinary universities of applied sciences, with over 14'000 students and 3'400 faculty and staff.

As one of the leading Engineering Faculties in Switzerland, the ZHAW School of Engineering (SoE) emphasizes topics which will be relevant in the future. Our 13 institutes and centers guarantee superior-quality education, research, and development with a focus on the areas of energy, mobility, information, and health.

The Institute of Data Analysis and Process Design (IDP) is a center of competence for the development and ap-plication of quantitative methods in the areas of data analysis and operations research. IDP is currently looking for an

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