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Are you passionate about applying quantum computing to addressing real-world challenges? Join us to develop quantum optimization methods that support the transition to sustainable and resilient
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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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-enhanced distributed MPC to improve computational speed, (2) cooperative approaches enabling dynamic collaboration among households, and (3) quantum-based MPC to potentially accelerate optimization tasks
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Engineering (FSE) contributes to this mission by training skilled professionals through our new EngD programme in Sustainable Process Design. This 2-year post-master design programme, closely collaborating with
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period of 4 years at the Eindhoven University of Technology, Department of Mathematics and Computer Science. The student’s working locations will be at Eindhoven University where the PhD candidate will be
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infections. As a post-doctoral researcher, you will work at the intersection of data science, epidemiology, and clinical research, developing innovative methods to optimize the use of rich real-world data. You
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We are seeking a highly motivated PhD candidate to join our research team in the field of mixed-signal IC design, focusing on the implementation of physics-based computing paradigm. The ideal
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perform a prospective trial at the Dutch Breast Cancer Screening Program to determine the impact on screening performance when optimizing the radiologist’s interpretation. This trial will involve two
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MSc degree in a relevant field, such as Operations Research, Operations Management, Industrial Engineering, Computer Science, or Machine Learning. Solid experience with quantitative optimization methods
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computational and experimental techniques in a high-tech industrial-academic setting. Develop constitutive material models tailored to recycled aluminum sheet forming, and implement them within commercial FE