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implementation in Fire Dynamics Simulator CFD code Experimental validation of simulations Machine learning for accelerated evaluation of radiative properties The doctoral degree will be awarded upon successful
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have good written and oral English skills. Please be aware that user experience with commercial CFD software (such as Fluent) is irrelevant for this position. Personal and relational qualities will be
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models for gases to solid particles Experimental characterization of fuel particles using FTIR Mathematical model formulation and programming Model implementation in Fire Dynamics Simulator CFD code
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to carry out high-performance numerical simulations using our in-house CFD code, extract physical insights from simplified flow models, and characterise synchronisation thresholds and the robustness
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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian ERI@N is seeking an experienced and motivated Research Associate to join
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develop computational fluid dynamic (CFD) tools that make exascale computing accessible to a broader set of users. The successful candidate will develop a massively parallel solver, capable of running
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technology for the green transition, marine hydrodynamics, hydrodynamic waves, and continuum mechanics. This project focuses on detecting underwater acoustics using AI methodologies. Additionally, CFD
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that are relevant to industry demands while working on research projects in SIT. The researcher will be part of the team of the MCCS NATURE Project (https://www.nparks.gov.sg/Cuge/Programmes-Schemes/Research
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cookie and refresh page to watch video, or click here to open video) About the position This PhD project is connected to FME NorthWind (https://www.northwindresearch.no/ ), a Norwegian national research
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at the university level; Expertise in CFD software (OpenForm, Ansys Fluent) andFEM software (ABAQUS, ANSYS, SAP2000) and coding (Python/MATLAB). Professional engineering licensure (HKIE/CEng