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Field
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, commonly referred to as neuromorphic computing holds the potential to create highly intelligent machines capable of supporting a wide range of everyday applications, from autonomous vehicles to smart
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Low Countries and of putting some of the historiographical and theoretical assumptions about the role of institutions, political participation and inequalities in urban societies to the test. The
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to drive an extremely weak parity forbidden transition. In order to detect the signals from driving such a weak transition, quantum entangled states will be used that reject external perturbations. Based
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make extensive use of low-fidelity simulations which can provide fast but inaccurate solutions depending on the flow complexity. To close this gap, this PhD will explore machine-learning (ML) methods
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. On the other hand, typical design cycles in industry still make extensive use of low-fidelity simulations which can provide fast but inaccurate solutions depending on the flow complexity. To close this gap
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infrastructure impacts the overall quality of life among low-income peri-urban communities. Your research should also contribute in selecting appropriate water and sanitation infrastructure that not only improves
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? Are you fascinated about sleep? In this project TU/e works together with Sleep Center Kempenhaeghe and Takeda to improve long-term, low-obtrusive monitoring of the sleep disorder narcolepsy and facilitate
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Your job Are you passionate about the future of blue biotechnology and eager to contribute to the fast-developing field of marine invertebrate cell culture? We are seeking a mission-driven
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neural control pathways (e.g., CPG-like and reflexive). Moreover, candidates will be required to develop reinforcement learning techniques to teach such neuromuscular models to execute a broad range of
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simulate ultra-low-power energy-harvesting and power-management ICs using CMOS technologies. Develop novel rectifier and MPPT architectures optimized for mechanical energy sources. Implement, tape out, and