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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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that activity-silent mechanisms, such as short-term synaptic plasticity, also play an important role. We will experimentally target these two mechanisms, using EEG in combination with machine learning to reveal
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Organisation Job description Project and job description This PhD position is dedicated to advancing autonomous robotic manipulation and control within a textile-sorting cell, where garments arrive
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score of at least 237 on the computer-based form of the Test of English as a Foreign Language (TOEFL); or A score of at least 92 on the internet-based test of the Test of English as a Foreign Language
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garments into recycle, reuse, and manual-review streams; this PhD project tackles the core challenge of designing and optimizing a high-throughput hyperspectral imaging system, fused with complementary
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- Excellent command of English language (both written and spoken) - Excellent command of (spoken) Dutch language or willingness to learn Dutch Additional Information Benefits We offer you following
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this initiative, 15 early-stage doctoral candidates (DCs) will be trained through a comprehensive, interdisciplinary program spanning material science, device physics, computer architecture, hardware prototyping
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this initiative, 15 early-stage doctoral candidates (DCs) will be trained through a comprehensive, interdisciplinary program spanning material science, device physics, computer architecture, hardware prototyping
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We are looking for a talented and enthusiastic candidate for a fully funded 4-year PhD position. The PhD candidate for this project will be working at the RNA Structural Ensemble Dynamics group led
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challenges holding back an even wider usage. This PhD position is part of the national NanoMedNL consortium that aims to counter these challenges and thereby accelerate and support the development of novel