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Field
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advancement of the research of deep neural networks, in the field of adaptive processing of graph data (Deep Graph Learning). The project includes the following strongly interconnected fundamental research
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yield new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at leveraging graph-theoretic approaches to analyze and predict food-effector
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France 91120, France [map ] Subject Areas: Applied Mathematics - statistical learning, graph learning or large language models Appl Deadline: 2026/03/24 03:59 AM (posted 2026/02/03 05:00 AM, listed until
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. Umeå University is offering a PhD position in Computing Science with a focus on machine learning for graph
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the form of graphs to analyze and predict food-effector systems. Key Responsibilities Develop Probabilistic Machine Learning Models to integrate graphs and food-related omics data Multi-omics integration
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some overlapping measures in the individual data sets and through the use of advanced analytic tools including machine learning and graph theoretics, one can discover multiple developmental pathways in
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-Neria Logic, set theory Shai Evra Graph theory, representation theory, number theory Adi Glucksam Complex analysis, potential theory, and dynamics Or Hershkovits Geometric analysis Mike
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Technologies for the Social Sciences (KTS), Team Information Extraction & Linking located in Cologne, is looking for a Research AssociateKnowledge Graphs (Salary group 13 TV-L, working time up to 100 %, limited
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Leibniz-Institute for Food Systems Biology at the Technical University of Munich | Freising, Bayern | Germany | 10 days ago
new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at leveraging graph-theoretic approaches to analyze and predict food-effector
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Infrastructure? No Offer Description Mission: Optimize graph databases, including research, implementation, experimentation and dissemination tasks. Functions to be developed: Analyze the state of the art in