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engineering Engineering » Simulation engineering Researcher Profile Recognised Researcher (R2) Application Deadline 6 Apr 2026 - 21:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 17 days ago
and Simulations Lab”. Where to apply Website https://jobrxiv.org/job/research-assistant-researcher/?utm_source=euraxess Requirements Additional Information Work Location(s) Number of offers
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NIST only participates in the February and August reviews. There is a growing need for high-performance materials for various technological applications. To address this need, the NIST-JARVIS (https
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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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atmospheric perturbations, and improving performance under realistic operational conditions. Main activities include: • Designing and developing deep learning models to correct wavefront sensor nonlinearities
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. Objectives: Characterize the hydrodynamics of the gas phase in bioreactors at different scales (20Là15m3) CFD simulation of gas/liquid flow using the Eulerian approach (two-fluid model) Comparison between
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) Online: https://www.uaa.alaska.edu/students/safety . Request a paper copy in person: UAA Police Department Office at Room 114 of Eugene Short Hall on the Anchorage campus / UAA Dean of Students Office at
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-of-the-art technology. Research the current state of metal hydride storage systems and select a suitable metal hydride for your simulation Create a model of the storage system in Aveva Process Simulation and
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machine learning (ML) approaches offer a powerful framework for modeling complex catalytic materials with near ab initio accuracy while enabling simulations at significantly larger spatial and temporal
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the molten pool. However, these models are computationally intensive and impractical for widespread simulations of large-scale part deposition. This project aims to develop a novel FEA-based approach