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in one of the following areas: Machine Learning / Information Retrieval / Knowledge Graph Representation / Recommender Systems Graph Theory/Network Science Python, and up-to-date machine learning
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Carolina is inviting applications of two postdoctoral associates in the area of mathematical foundations of data science, AI, Graph Theory, Optimization, Probability Theory in a broader sense. The candidates
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the contract starts; you can apply for these positions already before you have your degree. We value expertise in domains such as graph algorithms, parallel algorithms, computational complexity theory, models
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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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graph data, conclude research projects in a timely manner, write reports, and manuscripts. Engage in career development activities, apply for dedicated funding and contribute to lab-based grant proposals
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-learning methods, knowledge-graph and ontology-based scientific data infrastructures, and agentic workflows for autonomous hypothesis generation, mechanistic exploration, and design of catalytic systems
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Job Posting Title: Post Doctoral Scholar The Opportunity Lead and contribute research on multimodal data integration, ontology and knowledge graph building for energy domain. Supervise graduate and
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of SATURNA, namely Language Models for RNA sequences, Graph representation learning and generative models, Knowledge-Augmented RNA modeling, Computational RNA biology and Experimental stem cell biology and RNA
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brings together leading researchers in algebra, combinatorics and related disciplines, including finite geometry, algebraic graph theory, permutation group theory, coding theory and extremal combinatorics
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individuals with expertise in one or more of the following areas: Generative AI Agentic AI Graph Representation Learning and Modeling Foundation Models Large Language Models Multimodal Learning Forecasting