'BFH and the canton of Bern: It's the short (bike) routes from research and teaching to culture, politics and practice that I appreciate'. Maurizio Trippolini
Research Assistant in Machine Learning and Intelligent Maintenance
80 – 100 %
The position is initially limited to one year with the prospect of extension
Start by arrangement
Plenty of contact with eager young people from all over the world who are set on achieving things.
Great freedom in work organisation with lots of leeway for your ideas, your creativity and decisiveness.
Focus on research that is geared towards practical orientation and the education of committed people rather than mere profit maximisation.
Work place in prime location with excellent access.
National and international networks and contacts with business, economy, society and the political world.
What you'll be doing here
- Contribute to research projects in the field of condition based and predictive maintenance in collaboration with our industry partners
- Develop innovative approaches to data-driven maintenance using state-of-the-art machine learning and statistics approaches
- Develop and implement data-driven methods for the detection and diagnosis of faults in industrial assets and infrastructure
- Combine data science approaches and engineering domain knowledge
- Enjoy a stimulating and rewarding applied-research environment; Remote work and flexible working hours are possible
What you'll bring with you
- You hold an BSc degree in computer science, engineering, data science, physics, applied mathematics or are about to complete your MSc degree in one of these fields soon
- Strong background in machine learning and excellent analytical skills
- Strong programming skills, proficiency in Python; Good proficiency in state-of-the-art machine learning libraries
- Proficiency in written and spoken English; Strong problem-solving skills, highly motivated
- Please include your CV, copy of BSc & MSc thesis (if applicable), academic transcript incl. list of completed courses
School of Engineering and Computer Science
In the School of Engineering and Computer Science we don't move with the times, mostly we are a bit ahead of them! We find it fascinating what benefits technology can have in people's everyday lives. We gain knowledge through research and joint projects with industry and business. This exchange brings about cutting-edge insights that we continually share with students.
Quellgasse 21, 2501 Biel
P +41 31 848 43 49
Prof. Dr. Angela Meyer
P +41 32 321 64 69
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