20 bayesian-object-detection PhD scholarships at Delft University of Technology (TU Delft)
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modelling approach, and dynamic Bayesian Networks would be advantageous. Willingness to conduct research in a multi-national project team. Funding requirements: You cannot have resided in The Netherlands in
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superposition and entanglement to “large” objects that we usually think of as classical particles. This is exactly what you will do at TU Delft. As a PhD student in our teams, you will investigate how
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the vehicle fleet and the multi-objective design of the mixed transporation network. Our key hypothesis is that it is possible to design a mixed network by simulating how to serve a given demand with an
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missions have revealed that some icy moons of the outer solar system have oceans beneath their icy crust. These findings have broadened the definition of habitability and placed these objects at the center
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partners: ASML and DCODIS (a start-up). This is technically challenging applied research with as main outcome a proof-of-concept tool that allows developers to quickly find and fix software errors including
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aims to rethink how soft robots can interact with their environment, focusing on large-area, multi-point contacts—similar to how an elephant wraps its trunk around an object. Unlike traditional robots
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. This involves dynamic engagement like walking, observing, and handling objects. The relationship between perceptual experiences and the dynamic structures of the multi-sensorial information generated by active
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-classical “squeezed” states of motion. The next frontier is to extend quantum control to sensing applications that include detection of tiny recoils, from molecules of rarefied gases to potential dark matter
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. Change. Impact! Faculty Mechanical Engineering From chip to ship. From machine to human being. From idea to solution. Driven by a deep-rooted desire to understand our environment and discover its
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! Faculty Mechanical Engineering From chip to ship. From machine to human being. From idea to solution. Driven by a deep-rooted desire to understand our environment and discover its underlying mechanisms