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researchers in soft robotics, control theory, and machine learning. They will have access to a fully equipped lab and benefit from collaborations within the ERC team and across TU Delft. There will be
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questions. Given the uncertainties involved in food supply chains, we prefer candidates who have a background in (stochastic) optimization methods (e.g., machine learning, stochastic dynamic programming
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, you will explore how data-driven models capturing the state-of-health and degradation can be integrated in the battery model. You will develop these machine learning-based proxies together with a
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maintain robustness through evolution using live-cell imaging and multiscale modelling. Job description Cells are often described as intricate machines where proteins work together in a tightly coordinated
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these machine learning-based proxies together with a postdoctoral researcher working in this project (see below), leveraging data from experiments in our project. Third, you will explore how local connection
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includes PhD students and researchers at TU Delft, Wageningen University and Research, and Erasmus University Rotterdam, as well as industrial partners that specialize in machine learning, climate control
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intersection of mechanics, materials, and machine learning. Collaboration with international experts from diverse disciplines. Access to cutting-edge computational and experimental facilities. Supervision of MSc
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and an online learning platform with 100+ different courses; 7 weeks birth leave (partner leave) with 100% salary; partly paid parental leave; a pension at ABP for which UvA pays two third part of
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described as intricate machines where proteins work together in a tightly coordinated fashion to produce essential cellular functions. Yet evolution challenges this picture. Proteins that are crucial for a
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of the identified structures via stereolithographic, 3D printing and textile techniques like tufting, machine-based embroidery techniques or non-interlaced 3D pre-forming. Development of advanced imaging and