404 phd-studenship-in-computer-vision-and-machine-learning PhD positions in Netherlands
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Are you interested in writing to learn and learning to write in the age of AI? As a PhD candidate, you will investigate these topics at the intersection of (foreign) language learning and
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interested in writing to learn and learning to write in the age of AI? As a PhD candidate, you will investigate these topics at the intersection of (foreign) language learning and technological developments
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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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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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Centrum Wiskunde & Informatica (CWI) has a vacancy in the Machine Learning research group for a talented PHD-studenT iN NeuroAI of Developmental vision (m/f/x) Job description A PHD-studenT iN
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, computational design, and post-mechanical comfort systems in architecture. Where to apply Website https://www.academictransfer.com/en/jobs/354739/phd-on-computational-design-3d-… Requirements Specific
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funded PhD position invites applications from candidates interested in the intersection of computational design, robotic fabrication, and environmentally performative architecture. The research will
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8 Sep 2025 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Computer science » Computer hardware Computer science » Digital systems Engineering
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://www.academictransfer.com/en/jobs/354473/phd-on-computational-modelling-… Requirements Specific Requirements A master’s degree (or an equivalent university degree) in Chemical Engineering, Physics, Mechanical Engineering, or
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repaired, reused, or discarded requires sophisticated condition assessment and decision-making capabilities. This PhD project tackles a critical challenge: how to develop robust machine learning models