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for entry into a PhD program. A background in machine learning, inverse problems, scientific computing, or related data-driven methods is highly desirable. You are curious about combining physical modeling
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and analysis of dedicated algorithms for training analog circuits directly from data. In this PhD project, you will develop a novel system-theoretic framework for learning in analog circuits and
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at the intersection of computer vision, micro-electronics analysis, and hardware security, and will work under the supervision of researchers within the Department of Intelligent Systems. The PhD researcher will be
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low latency and high capacity optical switched AI computer network architecture empowered by the developed photonic integrated WDM switches and controls. The PhD candidates will contribute to the TU/e
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, Econometrics, and Equilibrium, Expectations & Dynamics (CeNDEF). Find more information … Where to apply Website https://www.academictransfer.com/en/jobs/363541/phd-candidate-in-aidriven-flood… Requirements
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partners in the Netherlands and abroad. You will work with large, multi-center clinical datasets and contribute to translating advanced computational methods into clinically relevant applications. This PhD
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information, please visit the Computational Imaging group page: www.cwi.nl/en/groups/computational-imaging Where to apply Website https://www.academictransfer.com/en/jobs/363520/phd-student-on-the-subject-of-i
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15 Aug 2026 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Computer science » Programming Engineering » Computer engineering Engineering » Electrical
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-wide traffic prediction Design physically consistent and interpretable machine-learning methods for dynamic traffic systems Test and validate prediction models using large-scale real-world traffic data
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Health Data Sciences and Informatics (OHDSI, https://ohdsi-europe.org ) initiative, dedicated to bring out the full value of observational health data through the OMOP Common Data Model and large-scale