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descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange isotherm parameters directly from molecular properties. These predictions will be integrated
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information about our institute here: https://www.fz-juelich.de/en/ias/ias-8 Your Job: Develop physics-aware simulations of growing cell populations, including their spatiotemporal manipulation in microfluidic
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numerical simulations to reproduce and predict magnetically confined fusion plasma experiments 2.Development of transport models based on simulation data and their implementation into integrated transport
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
is also leading the development and validation of novel machine learning methods for LEGEND simulations and analysis. We have been heavily involved in constructing, commissioning, and operating
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the project SOMIPs - Simulation, Optimization and Monitoring using AI-based Digital Twin Technology for Incineration Plants The call is governed by this Notice of Opening, the University of Coimbra Research
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opens a call for the assignment of a research grant, with one position(s), under the project SOMIPs - Simulation, Optimization and Monitoring using AI-based Digital Twin Technology for Incineration Plants
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be submitted through the university’s online recruitment site: https://www.uvmjobs.com . Nominations and inquiries should be sent to Peter Newman at Peter.Newman@uvm.edu and copy Crispina Pincus
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Your Job: At the Institute for Advanced Simulation – Data Analytics and Machine Learning (IAS-8) we are looking for a PhD student in machine learning to work within a project linked to the
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formalized in the online application submission system, available on FMUP's webpage: https://sigarra.up.pt/fmup/pt/CNT_CAND_GERAL.CONCURSOS_LIST (Ref. 2026/16, Pr. 414). 11.3. The application is accompanied by
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the behavior of complex rotating machinery operating under extreme conditions. Through the integration of modeling, simulation, and experimental validation, the group supports the design, performance