School:

School of Engineering

Starting date:

1.9.2024

Your role

In collaboration with the Aerospace Structures & Materials (ASM) Department at the Delft University of Technology (TU Delft) and the company Hitachi Energy, we are now looking for an outstanding Ph.D. student.

The focus of the Ph.D. will be on physics-informed deep learning algorithms for acoustic diagnostics and prognostics of complex systems. This includes exploring how novel neural network algorithms can exploit physics and engineering knowledge of the system together with available acoustic data to improve acoustic diagnostics and prognostics.

• You will develop innovative approaches using state of the art statistical, machine learning and deep learning methods algorithms for detection, diagnostics and prognostics of incipient failures in industrial assets.
• You will combine engineering knowledge with data-science techniques (physics-informed machine learning).
• You will closely collaborate with our industry partners in order to implement your algorithms in the operational environment.
• The focus of your work will be on algorithm research and development, with relatively little data management/engineering.
• You will have the opportunity to co-supervise student research projects.
• You will be supported by experienced colleagues from the team in order to further develop your technical and scientific skills.
• Your daily work will typically allow for a high level of flexibility and freedom.

Your profile

• You have a master degree in engineering, physics, computer science, statistics, applied mathematics or a related discipline.
• You have programming experience in Python. Experience with TensorFlow and PyTorch is an advantage.
• You have experience with applying data analytical and machine learning methods.
• Experience with deep leaning algorithms is advantageous.
• You have high oral and written communication skills in English.
• You are curious to learn and develop new methods and algorithms and apply them in real industrial systems.
• You are motivated to develop your personal research skills, coached by experienced researchers.

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.

ZHAW is committed to gender-mixed and diverse teams in order to promote equality, diversity and innovation.

As one of the leading Engineering Faculties in Switzerland, the ZHAW School of Engineering emphasises topics which will be relevant in the future. Our 14 institutes and centres guarantee superior-quality education, research and development with an emphasis 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 application of quantitative methods in the areas of data analysis and operations research. The Smart Maintenance Team of the IDP develops innovative solutions for intelligent condition monitoring, fault detection, diagnostics and prognostics of technical equipment.

What you can expect

We offer working conditions and terms of employment commensurate with higher education institutions and actively promote personal development for staff in leadership and non-leadership positions. A detailed description of advantages and benefits can be found at Working at the ZHAW . The main points are listed below:

Contact

Dr. Manuel Arias Chao

Jocelyn Schaad
Recruiting Manager