36 computer-programmer-"IMPRS-ML"-"IMPRS-ML"-"IMPRS-ML" positions at University of Twente in Netherlands
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Regions, Smart Industry and Sustainable Resources. Our faculty is home to about 2,900 Bachelor's and Master's students, 550 employees and 150 PhD candidates. Our educational and research programmes
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. resilient infrastructure systems 2. value-based project and programme delivery of infrastructure assets. In this project we will closely collaborate with the Tilburg School of Economics and Management
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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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environment that encourages professional growth, mentoring, and a healthy work–life balance. About the organisation The faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) uses
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. The project will be carried out in collaboration with an industrial partner under the umbrella of the Industrial Focus Group XUV Optics where a multidisciplinary research program on growth, characterization
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be carried out in collaboration with an ASML Berlin under the umbrella of the Industrial Focus Group XUV Optics at the university of Twente where a multidisciplinary research program on growth
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Biomedical Signals and Systems (BSS) group of the department of Electrical Engineering at the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS). As a PhD candidate, you will be
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analysis, and high-performance simulations? We offer a challenging PhD position in the Mathematics of Computational Science group to design and analyse novel structure-preserving methods for stochastic
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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