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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 literature and blind rehabilitation. Of 101
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Science, such as: Optimization, Machine Learning, Statistical Learning, Applied Probability, Graph Theory and Network Science, or Computational Statistics, with opportunities for cross-disciplinary
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analysis, complex analysis, partial differential equations, functional analysis, graph theory or similar areas depending on the evolving needs of the department. The successful candidates are also expected
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) Experience with modern deep learning frameworks (e.g., PyTorch, JAX, TensorFlow) Background in at least one of the following: graph learning, scientific computing, surrogate modeling, or ML theory Interest in
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on), machine learning, optimization, functional analyses Related Keywords: linear algebra, mathematical statistics, graph theory, manifold theory, other mathematical science domains 3.The successful applicant
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as (1) Problem Solving and Critical Thinking (Inductive and Deductive Reasoning); (2) Set Theory; (3) Logic; (4) Algebra; (5) Graphs; (6) Theory of Integration and Differentiation; (7) Functions
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-dimensional probability, random matrix theory, random graphs, stochastic analysis, and stochastic processes. Preference will be given to applicants with demonstrated research interests or expertise in
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main areas of research are machine learning, distributed systems, and the theory of networks. Within these three areas, we are currently working on several projects: graph neural networks, natural
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(CBA). Performs other duties as assigned. Additional Job Description Required Qualifications: Ph.D. in Data Science, Analysis, Graph Theory, Algebra, Combinatorics, Applied Math or Statistics, or related
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relevant expertise: A PhD in Computer Science or a closely related field, with specialization in Quantum computing and Graph theory In this role, you will be responsible for conducting research on graph