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). For more information: https://www.cordis.europa.eu/project/id/101225380 Research focus The PhD candidate will work on one or more of the following interconnected areas: AI‑ and machine‑learning‑based
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | about 1 month ago
the communication and storage needed to retain most of the information. Environment. The PhD will take place at Inria Grenoble, in the Thoth team. This is a large team focused on machine learning, and
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. Please do not contact us for unsolicited services. Where to apply Website https://www.academictransfer.com/en/jobs/360266/phd-position-probabilistic-infe… Requirements Additional Information Website
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of cryo-electron tomography (cryoET), molecular dynamics simulation, and machine learning. The project aims to develop AI methods for mesoscale structural biology, understanding how cellular macromolecules
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of Computer Science at UNNC is developing strong research in areas including Big Data and Visual Analytics, Computational Intelligence, Machine Learning, Software Implementation and Testing, and their applications in
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conservation, and aid authentication. Modern scientific imaging techniques now generate large volumes of complex data that can reveal new insights for art historians, conservators, and the broader public. Among
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to make a start with your teaching portfolio and dedicate 10% of your working time to teaching in the psychology curriculum. Would you like to learn more about what it’s like to pursue a PhD at Radboud
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2 Apr 2026 Job Information Organisation/Company University of Galway Research Field Computer science » Computer systems Researcher Profile First Stage Researcher (R1) Positions PhD Positions
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mathematics (diploma or master's degree) German language skills, if not first language: C1 Good computer skills Desired: PhD-theses in mathematics education Desired: Professional experience in teaching
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, SIAM Review, 60(3):550–591 (2018). [4] Diederik P Kingma and Max Welling, Auto-Encoding Variational Bayes, International Conference on Learning Representations (ICLR) 2014 ArXiv. http://arxiv.org/abs