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probability, random matrix theory, random graphs, stochastic analysis, and stochastic processes. Preference will be given to applicants with demonstrated research interests or expertise in the development
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to implement and optimize AI/ML models for biomedical datasets. Preferred Knowledge, Skills and Abilities Mathematical Modeling: Strong foundation in numerical modeling, graph theory, and statistics. Algorithm
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natural laws, scientific theories, commonsense facts, and regulatory constraints. These systems have capabilities to explain their outputs by how they reason based on knowledge, that understand risks and
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computer science using data-driven techniques (graph theory, ICA, machine learning), in other imaging modalities (DTI; MEG), and in multimodal integration will be relevant. Experience with AFNI/SUMA, SPM, FSL
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, animations, interactive charts, graphs, and video-based scenarios) accurately. Duties & Responsibilities Create high quality supporting materials including participant guides, leader guides, story boards
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has a strong PhD program in Applied Mathematics, Applied Statistics, Graph Theory/Combinatorics, and Analysis, featuring active research collaborations both within the University and with external
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research areas in the Department, such as analysis, applied mathematics, graph theory, number theory, or data science; and 3) provide service to the academic unit. Required Education and Experience
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communities. Our founding motto, LIVE TO THE TRUTH, was said at the end of each class by beloved first principal, Cyrus Peirce, who sought to discover and teach "truth in theory and principle...truth in spirit
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in the following areas: Deep Learning, Scientific Machine Learning, Stochastjc Gradiant Descent Method, and Numerical PDE’s - Advised by Dr. Yanzhao Cao Probabilistic Graph Theory (Network Traversal
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research and publication. Additional Job Description Required Qualifications Ph.D. in Data Science, Analysis, Graph Theory, Algebra, Combinatorics, Applied Math or Statistics, or related area from a