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systems with a particular emphasis on methods and systems that cope with imperfect knowledge and uncertain sensors. The research environment provides excellent opportunities for open-minded co-operation
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consists of three major parts: sensor printing, circuit design and integration and developing of an AI algorithm and using it to teach the sensor to selectively measure desired gases . In this role, you will
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chemical reactions and assembling functional nanomaterials from bottom-up in scanning tunnelling microscopy (STM). The project is tightly linked to machine learning algorithms in images (image classifier
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aims to optimize the operations (serving) of AI by developing algorithms that manage compute, network, and storage resources in a carbon-efficient way while supporting long-term benefits
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aims to optimize the operations (serving) of AI by developing algorithms that manage compute, network, and storage resources in a carbon-efficient way while supporting long-term benefits
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models. Having enthusiasm in control and a good balance between theory and practice is essential. Good programming skills also support the development of digital twins, soft sensors, ML-supported control
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following topics: Hydraulic and pneumatic applications Machine components (e.g. bearings, actuators, sensors) Power trains (e.g. electro-mechanical, electro-hydraulic, hydraulic) Industrial machinery Your
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, estimation, and identification algorithms that directly interface with physical hardware. We work closely with industry partners. Our research has led to several methods now used in commercial products. We
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are looking for a skilled experimentalist who would perform technically challenging swimming force experiments with tiny living organisms using a micropipette force sensor (Backholm et al ., Nature Protocols
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would perform technically challenging swimming force experiments with tiny living organisms using a micropipette force sensor (see Backholm et al ., Nature Protocols 2019 https://doi.org/10.1038/s41596