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and compare energy consumption at different scales (building, block, neighborhood, city). 2. Produce relevant analyses and indicators for decision support Generate metrics, maps, graphs and
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with expertise in Combinatorics and Graph Theory. DEPARTMENT: The mathematics program at Otterbein is unique in that mathematics majors begin, in their first semester, a study of advanced calculus and
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, demographic, forest, and supplier data. The work includes constructing and processing heterogeneous spatial-temporal and supplier datasets; designing knowledge-graph-based data models for integrating diverse
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services utilization, maternal and infant health outcomes, and racial and social inequities and summarize results from analyses into data tables, graphs, figures, and presentations. They will support
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clustering, entropy metrics, and graph-based representation of tumor architecture. Dimensionality reduction and feature stability analysis will be performed using correlation filtering, stability selection
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, or materials informatics. Familiarity with explainable AI or counterfactual explanation methods. Experience with molecular dynamics data, graph neural networks, or multi-component system modelling. Track record
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of groups that are of interest in the context of rigidity, group cohomology, noncommutative geometry and index theory, harmonic analysis on groups, expander graphs and high-dimensional expanders. Required
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. A particular focus of the project will be on: 1) Graph Neural Networks for cosmology, neutrino and/or collider physics, 2) Domain adaptation methods / model robustness, 3) Uncertainty quantification
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graphs and related structures, limit theorems, stochastic calculus and applications, for example in machine learning and mathematical statistics Participation in the scientific activities of the department
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for users of the Monarch Android pin‑array tablet (https://www.humanware.com/en-usa/monarch ). In this role, you will work closely with Humanware’s ML developers to design and implement an ML toolchain