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10-100 nm would be required, varying in absolute value over the surface of the wafer. An elegant method to correct wafer position is to include an adaptive element into the wafer stage, which allows
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, the challenge is to develop, validate and test a method that offers personalized, tailored travel and route advice in order to stimulate cycling. This four-year PhD project is part of Horizon Europe project Bio
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, integrating AM into supply chains demands new models and methods. In this PhD project, you will: develop dynamic supply chain design models that enable the repositioning of AM equipment based on Defence
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importance. Acoustics-based diagnosis, using an array of microphones, is a promising method to identify faults, as sensing on the moving components in these high tech systems is not possible. The challenge is
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: Deep learning Medical image computing (preferably x-ray imaging) Computationally efficient deep learning Deep learning model generalisation techniques Translating deep learning models into clinical
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learning Medical image computing (preferably x-ray imaging) Computationally efficient deep learning Deep learning model generalisation techniques Translating deep learning models into clinical settings
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, in collaboration with the NanoElectronics (NE) group at the University of Twente and the Infomatter group at AMOLF. The SMIP project aims at revolutionising computing by developing adaptive, smart
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Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Job description
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models aligned with EU Packaging and Packaging Waste Regulation (PPWR) targets. Your role Work primarily at FIP-AM@UT, applying advanced computational and experimental techniques in a high-tech industrial
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++ programme “Break-through technologies in flow and fluid composition measurement”. It involves close cooperation with flow sensor companies and the TU Delft, where a post-doc will focus on the electronic