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Field
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background in linear algebra, finite fields and rings; Strong background in digital hardware design and design automation; Excellent hardware design, programming, and debugging skills; Experience with computer
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a similar field; Strong mathematical background: basic knowledge of graph theory and excellent background in linear algebra, finite fields and rings; Strong background in digital hardware design and
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, or a similar field; Strong mathematical background: basic knowledge of graph theory and excellent background in linear algebra, finite fields and rings; Strong background in digital hardware design and
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understanding of lithium mineral systems is clearly needed to support exploration efforts for this energy critical metal. The PhD student will explore the geochemical behaviour of lithium in the Earth's crust as
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machine learning solutions to optimize the component lifecycle directly contributing to a more circular economy. Information In the manufacturing landscape, determining whether a component should be
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the Dutch research council (NWO). You will be part of a team with another PhD student and two consecutive postdoctoral researchers, supervised by Dr. Tim van Erven. This is what you will do: AI and machine
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of metal electrodeposition is largely lacking. Knowledge gaps remain on the exact mechanisms of conversion from solid oxides to metallic iron, as well as the exact physics and operation parameters
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development in repair and remanufacturing, allowing for longer product lifetime and promoting a more sustainable and circular economy. This project investigates and integrates two crucial elements
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interactive component. The position is with Prof. dr. Cees Snoek, Professor, head of the Video & Image Sense lab (VIS lab), at the University of Amsterdam. VIS lab is a world-leading lab on Computer Vision and
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at large, with a focus on collaborative, data driven, computational and intelligent systems, all with a strong interactive component. The position is with Prof. dr. Cees Snoek, Professor, head of the Video