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Field
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to identify that set, in co-creation with stakeholders. The second sub-project, a postdoc track, focusses on pedagogies or structures for guiding students in selecting competencies to be achieved as learning
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science, computer science, applied mathematics or a related field a strong background in machine learning, material modeling, and metals processing, modeling and simulation (This will be a clear advantage
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. This paradigm enables algorithms to securely access and process data within the environments where it resides, supporting federated learning for training machine learning models without moving sensitive or large
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analog circuits for implementing ONNs for computing. Modeling, simulate and benchmark different computing tasks such as sensor data processing. Explore ONN implementation topology and its energy efficiency
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for implementing ONNs. Modeling, simulate and benchmark different computing tasks such as combinatorial optimisation tasks and solving partial/ordinary differential equations with ONNs. Design and tapeout ONN chips
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of the PhD community of Naturalis and Biosystematics (WUR)— a close-knit group of PhD candidates and postdocs with whom you can share experiences and participate in training sessions, workshops, and
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Examination (HINE). However, current predictive models lack integration of these modalities and precision in individualized diagnosis and prognosis. As part of the ENSEMBLE Project—a multinational study funded
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culture of mutual support and collaboration between researchers. CML has two Departments: Industrial Ecology (CML-IE) and Environmental Biology (CML-EB). Presently, about 150 fte (including postdocs and
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support each other. This necessitates a multidisciplinary approach bringing together optimization, machine learning and behavioral modeling methodologies. In the FlexMobility project we propose a holistic
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candidate, you will investigate the learning capabilities of feed-forward and recurrent models of neural circuits with various degrees of biological plausibility, with a focus on: Transferability of