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Field
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computationally efficient reduced-order dynamical systems on graph with modern power grid systems as an application. Education and Experience: Applicants must have recently completed a Ph.D. and have exceptional
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and collection, causal inference, network analysis, graph theory, visualizations, and online tool development. Experience in conducting online controlled experiments is also desired, but not required
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
generative models and/or graph neural networks. Domain knowledge of Mechanical Engineering problems is not required. The ability to transfer your knowledge to Engineering problems is however expected. Please
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. Experience with Bayesian methods, graph/network analytics, reinforcement learning, or other advanced AI approaches relevant to industrial systems. Experience with geospatial analysis, spatial data integration
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., MATLAB, Python, R) preferred. Solid background in signal processing, statistics, or computational neuroscience, preferred. Outstanding presentation skills, preferred. Experience in graphing, statistical
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the theory of quantum graph states. Additional expertise in computational methods would be useful but is not necessary. The Postdoctoral and Senior Research Associate positions will also involve
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accuracy in link-tracing designs (e.g. Respondent driven sampling) Partial graph data collection strategies for networks (e.g. Aggregated Relational Data) Large scale models for anomaly detection on graphs
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storage and analysis solutions (e.g., key-value stores, object or document storage, graph analytics systems) deployed on HPC computational and storage systems. Co-authorship of peer-reviewed publications
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, containerization (Docker), Kubernetes API development and web-based analytics tools Systems, Optimization, and AI ML/AI for mobility prediction and optimization Graph algorithms, network science Spatiotemporal
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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