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constitutive modeling and machine learning: how to ensure adherence to physical constraints when enhancing complex constitutive models with neural networks; how to extract interpretable equations from
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Internal Number: 6822606 Senior Network Engineer Posting Number: 73-2024 Department: Networking Services Employee Group: Professional/Technical Status: Full-time Starting Salary Range: Low 90's to High 90's
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symptom networks; and Preferred skills in programming, quantitative analysis, and handling complex datasets. Strict MSCA eligibility requirements: You must not hold a doctoral degree at the date
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university. We are willing to support applications related to our research on complex systems, network and data science, agent-based models, statistical physics, or computational and mathematical modelling
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University of California San Francisco | San Francisco, California | United States | about 1 month ago
participate in the resolution of complex technical issues in a timely manner while delivering best-in-class wired service support across UCSF. This role will conduct day-to-day network engineering and technical
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to join our team. The Centers for Disease Control and Prevention (CDC) are funding MICOM as part of InsightNet, an outbreak response network, with the goal of using data and analytics to support decision
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understanding of data evaluation, modeling, and interpretation of complex datasets Ability to work independently as well as collaboratively in an interdisciplinary and international research environment Very good
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, potentially reducing NOx emissions. Developing porous burners requires understanding complex physics such as heat conduction, radiative transfer, flame stabilization, and surface chemistry, which are difficult
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networks, graph neural networks, transformers, convolutional defiltering methods, etc.) for the integration in multi-physics simulation codes You will develop code for and run large-scale multi-physics
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? Set up a network model to reproduce the main results and provide potential neuronal mechanisms. Existing recordings with optogenetic inactivation could be leveraged to causally verify or reject important