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to students pursuing degrees through the doctoral level. More than 20 percent of its 25,000 students are enrolled in graduate course work, studying in disciplines ranging from atomic physics and graph theory
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. You will: Develop and apply novel graph learning based methods for predicting the synthesisability of organic molecules Develop and apply novel neurosymbolic AI methods to chemical problems If appointed
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complexity, approximation algorithms, extremal combinatorics, structural graph theory, and related fields. Qualifications and personal qualities Applicants must hold a master's degree or equivalent education
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and interdisciplinary data integration develop new AI-based methods, tools, scripts, ontologies and a knowledge graph based on RTG research results and relevant literature provide methodological support
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learning-based methods and interdisciplinary data integration develop new AI-based methods, tools, scripts, ontologies and a knowledge graph based on RTG research results and relevant literature provide
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are looking for strong candidates who would complement and/or strengthen existing research areas in our department (which currently includes discrete mathematics, optimization, graph theory, algorithms
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degrees through the doctoral level. More than 20 percent of its 25,000 students are enrolled in graduate course work, studying in disciplines ranging from atomic physics and graph theory to medieval
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atomic physics and graph theory to medieval literature and blind rehabilitation. Of 101 graduate offerings available, 30 lead to a doctoral degree. Connections working at Western Michigan University More
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, Computational Social Science, Big Data. Relevant skills could include statistical analysis, data management and collection, causal inference, network analysis, graph theory, visualizations, and online tool
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include statistical analysis, data management and collection, causal inference, network analysis, graph theory, visualizations, and online tool development. Experience in conducting online controlled