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to the School's research efforts in combinatorics. This role involves working on a project concerning fractional edge decompositions of graphs, addressing well-studied open problems, and exploring related variants
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This is a post-doctoral position in geometric graph
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 29 days ago
of more than 700 macromolecular complexes (~5.5 bilions of frames) [1]. DynaRepo is the first MDDB node in France: https://dynarepo.inria.fr/ . ComPASS, a graph-based method for identifying communication
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departments and organizations. Coaches RA I and RA II, interns, Co Ops on basic lab techniques. Calculates, graphs and compiles data obtained, maintaining records and logs of work performed; uses computer to
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Shai Evra Graph theory, representation theory, number theory Adi Glucksam Complex analysis, potential theory, and dynamics Or Hershkovits Geometric analysis Mike Hochman Dynamical systems
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ancestral recombination graphs to study of the genetic basis of diseases, incorporating ancient genomes • Apply and develop methods for partitioning heritability and estimating genetic correlations • Develop
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/knowledge graphs, and carbon accounting. The Research Fellow will help develop and lead the CognitionX Lab (https://cognitionx-lab.github.io/ ) with Dr. Jinying Xu, Assistant Professor and Director of
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description 1 Postdoctoral Researcher position in line: "Ontologies and Knowledge graphs for semantic interoperability
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/ Knowledge Graph Representation / Recommender Systems Graph Theory/Network Science Python, and up-to-date machine learning libraries Excellent written and verbal communication skills Track record of publishing
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an excellent publication record. Solid research experience in one or more of the following topics is expected: Graph neural networks Optimization algorithms Predicting structured output Self-supervised learning