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Field
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Job description Consortium This position is part of a European Doctoral Network consortium "Machine learning for integrated multi-parametric enzyme and bioprocess design", where 15 doctoral projects
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. The high-level goal of the project is simple: to use anatomical knowledge and existing knowledge as training data for deep neural networks (instead of manual annotations). The research will be conducted
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, fabricating, and characterizing effective memristive devices, with the goal of forming device networks for realizing the physical learning paradigm developed at AMOLF. You will integrate these memristive
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. Process driven research activities are performed in the field of chemical and biochemical systems, mechanical and electric systems and system networks. Typical product sectors include biobased products
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. Are you eager to work with a like-minded persons on a society-defining challenge? Keywords: Carbon capture; Electrochemistry; Proton-Coupled Electron transfer; Climate change mitigation; Professor
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environment with an open culture, where you can be yourself and we pay attention to each other and to the world around us. Make the most of our bicycle budget, or join networks such as Young@EUR Opens
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seeking a highly motivated PhD student to join our team to work on the design and implementation of Oscillatory Neural Networks (ONNs) for physics-based computing applications. You as the candidate will be
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seeking a highly motivated PhD student to join our team to work on the design and implementation of Oscillatory Neural Networks (ONNs) for physics-based computing applications. You as the successful
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researchers. CML has two Departments: Industrial Ecology (CML-IE) and Environmental Biology (CML-EB). Presently, about 150 fte (including postdocs and PhDs) are employed at CML. CML further collaborates with TU
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. Process simulation software is being developed for virtual optimization of tool design and material handling, enabling first-time-right manufacturing. The predictive quality of these tools relies