PhD candidate / Research assistant in transfer learning

’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

• An almost unbelievably large variety of themes and topics and a great mix of research and teaching.
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• Great freedom in work organisation with lots of leeway for your ideas, your creativity and decisiveness.
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• Responsibility in hugely exciting projects for the future attracting attention beyond the professional world.
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• Working with smart people of different professional backgrounds who want, like you, to do things and make a difference.
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• Plenty of contact with people from all over Switzerland and the world at large.

• You are developing transfer learning and domain adaptation algorithms to enhance the reliability of power system assets
• The project goal is to develop predictive maintenance algorithms that improve the reliability of fleets of industrial assets
• Our group offers a stimulating interdisciplinary research environment and a strong network with industry partners
• The position is part of the Swiss National Science Foundation project "Artificial intelligence for improving the reliability and resilience of industrial fleets"

• MSc in computer science, engineering, applied mathematics, physics, or a related field
• Strong experience in deep learning, transfer learning and domain adaptation, learning theory
• Ideally, you are familiar with power system infrastructure for power generation and storage
• You are self-driven and you have a strong publication record
• Your application should include a CV, publication list, research statement explaining your project idea and previous work, contact details of 3 referees

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.

Doing something meaningful in a fascinating environment and with an outlook to the future: a job at Bern University of Applied Sciences makes perfect sense. We’re busy researching, developing and virtually bending our minds to come up with practical solutions for business, culture and people in Bern, in Switzerland and all over the world. Apart from being incredibly interesting, this is also a lot of fun, and we get to learn a lot as well. This cutting-edge knowledge benefits all who are studying here or doing part-time continuing education courses. We have great plans for the future: We’re building two campuses and combining our strengths. So we’re creating the ideal environment for your future job with us.

Berufseinsteigende

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Berufseinsteigende

deutsch

Berufseinsteigende

deutsch