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Field
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seek a PhD candidate to work on representation learning methods on graphs for modeling static and temporal networks, with applications to ecological systems and beyond. The project will focus
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-learning models (e.g., graph neural networks, equivariant architectures) in collaboration with computer science researchers. Applying developed models to problems in Earth and planetary interiors, such as
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | about 1 month ago
retrieval: reconstructing the original digital data from the sequenced symbols. This PhD project focuses on the first and fourth challenges, by developing joint compression and error-correction algorithms
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health. The ideal candidates will possess a doctoral degree (PhD or MD) and have experience with publications. In addition to dedicated project/experimental procedures, the Postdoctoral Research
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Committees in both the admission of graduate students and the day-to-day administration of the MSc and PhD graduate student programs. Including advising prospective students, admissions, awards, interpretation
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, graph theory, graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and supported by the COMMLab, the 6GSPACE Lab, the HybridNetLab, the QCILab
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cloud-based storage and service tools is helpful Preferred Qualifications: MS or PhD in a relevant field Experience with network neuroscience, graph theory, or connectomics Familiarity with high
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Campus (LLEC). Development of physics-informed and graph-based machine learning methods for energy system monitoring, forecasting, and planning Data analysis considering uncertainties, missing data
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in generating answers in the form of answer maps. You will explore these challenges together with the Principal Investigator as well as a postdoctoral researcher and two PhD candidates. We are looking
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(R2) Positions PhD Positions Application Deadline 29 Jul 2026 - 23:59 (Europe/Warsaw) Country Poland Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 1 Oct 2026 Is