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. Located in Ithaca, NY, the department has state-of-the-art equipment and facilities including studios, labs, two fabrication studios, a design materials library, 3D body scanner and multiple gallery spaces
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integrating local flexibility markets through distributed AI-based coordination, market mechanism design, and cloud-to-edge computing. It aims to develop scalable machine learning methods for coordinating grid
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under the “Cryptographic elements of trustworthy AI” project. The main research objectives for the project are the following: Analyze security of Machine Learning (ML) models against data modifications
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carbonate stratigraphy, structural geology fundamentals, and manipulation of seismic data. Formalized training on the use of machine learning and AI workflows that can be transferred to geoscience
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to design. Located in Ithaca, NY, the department has state-of-the-art equipment and facilities including studios, labs, two fabrication studios, a design materials library, 3D body scanner and multiple
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modeling, multilevel (random effects) modeling, and analysis of data from complex samples Experience with management and analysis of big data Experience with machine learning and related approaches (e.g
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required. Experience with finite-element method (FEM) and boundary-element method (BEM) is required. Experience with supervised machine learning in aeroelasticity is required. Programming skills, e.g
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geothermal resources, reservoir modeling, techno-economic analysis and machine learning implementation, and other emerging geothermal energy-related topics. The selectee will be expected to develop funding and