Senior Lecturer in Machine Health Intelligence 80-100 %
Join us in shaping Machine Health Intelligence research. You will combine AI with engineering insight to build innovative real‑world solutions for machine condition monitoring and optimization and teach engineering and data science students.
School
School of Engineering
Your role
* Research and development: you will take strategic and scientific responsibility for the further development of the Machine Health Intelligence domain within the Institute for Data Science. As an independent investigator, you will establish and lead your own research line and actively acquire third‑party funded research projects in collaboration with industrial and public partners. You will initiate, manage, and execute applied research and development projects in areas such as Intelligent Condition Monitoring, Predictive Maintenance, Machine Prognostics and Health Management (PHM), data‑driven diagnostics, reliability engineering, and optimization‑based decision support. You will publish your results in journals and present them in conferences (Innosuisse, EU, SNF, etc.).
* Teaching: you will design and deliver core and advanced courses at Bachelor's and Master's level. You will supervise project work, Bachelor's and Master's theses, and contribute to the continuous development of the study programmes at the intersection of machine health and AI. You will contribute to the strategic development of continuing education formats, including CAS programs in Predictive Maintenance and related fields, and actively maintain a strong professional network across academia and industry.
* Collaboration: you will actively design the further development of the Machine Health Intelligence research team.
Your profile
* You hold a doctoral degree in engineering, physics, applied mathematics, data science, or a closely related field, with a strong research background in one or more of the following: Anomaly detection in physical or technical systems; Machine condition monitoring, diagnostics and prognostics; Reliability and degradation modelling; AI‑driven operational decision‑making for complex technical systems; Physics‑informed machine learning; Industrial AI and digital twins.
* You have at least 3 years of experience in R&D in related fields, preferably in industry or the public infrastructure sector.
* You have demonstrated success in acquiring and managing externally funded research projects. A strong publication record in relevant journals and conferences is expected.
* You combine scientific excellence with practical orientation and are interested in translating advanced methods into industrial impact.
* You are passionate about transferring your knowledge and expertise to a next generation of engineers and data scientists, ideally with teaching experience in higher education.
* You are fluent in English and German.
Benefits
* Strong industry partnerships
* Applied research with real‑world impact
* Academic freedom to shape your research line
* Interdisciplinary collaboration within data science and engineering
* Design and shaping of education programmes at the intersection of data science and engineering
* A high degree of flexibility in working times
Our Commitment
ZHAW is committed to gender‑mixed and diverse teams in order to promote equality, diversity and innovation.
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.
Contact
Dr. Manuel Arias Chao
Senior Lecturer, Machine Health Intelligence
Jasmin Strobel
Recruiting Manager
Zurich University of Applied Sciences ZHAW
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