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models struggle to quantify uncertainty, risking overconfidence in volatile scenarios. The goal is to scale and enhance Bayesian Distribution System State Estimation using both simulated and, if necessary
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machine learning and computer simulations. The focus of the PhD project will lie on developing machine learning models for clustering, classification, regression and reinforcement tasks to work with
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collaborators. The activities will include: • Electromagnetic modeling and numerical simulations (e.g., FDTD, FEM) • Design of metasurface architectures based on dielectric materials available at CRHEA
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rules in networks of complex spiking neuron models in the application field of geolocalization: Building up simulation model for networks of complex neurons with topologies close to neuroscience models
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of Pisa) and Dr. Stan Van Gisbergen (SCM, Holland) https://www.scm.com/ , who will also serve as industrial mentor. DC9 - Objectives: Apply Machine Learning force fields and sampling methods to model bio
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Keen to push the frontiers of multiphase reactor modeling and accelerate the scale-up of emerging net-zero technologies? Join us at the Department of Chemistry and Chemical Engineering! About us Our
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biologic therapy, integrating data from clinical trials and real-world studies. The model will be used to simulate and evaluate optimized dosing strategies for special populations, including hard-to-treat
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Position in Theoretical Quantum Many-body Physics and Quantum Sensing at Indiana University Bloomington Fields: Quantum many-body theory, AMO–condensed matter interfaces, advanced numerical simulations
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of Campus Security Policy and Campus Crime Statistics Act. A hard copy can be obtained from one of the Campus Safety Offices. Please contact any of the Campus Safety Offices for any questions. https
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-cell transcriptomics and modern statistical/AI methodology to address this gap using in-house developed cell atlases. We will develop and benchmark approaches that infer copy-number changes and CIN