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in the area of Computational Fluid Dynamics. Familiarity with response surface modeling and optimization, is a plus. Experience using commercial codes like ANSYS-FLUENT is desirable. Qualifications
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modeling and optimization, is a plus. Experience using commercial codes like ANSYS-FLUENT is desirable. Qualifications An Associate Research Scientist/Scholar typically holds a PhD or equivalent terminal
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into disease mechanisms, identifying novel biomarkers and developing state-of-the-art predictive models for disease onset and progression. These models are translated into personalized prevention strategies and
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this data and advanced AI, medical, and computational models to generate insights into disease mechanisms, identifying novel biomarkers and developing state-of-the-art predictive models for disease onset and
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computational models to generate insights into disease mechanisms, identifying novel biomarkers and developing state-of-the-art predictive models for disease onset and progression. These models are translated
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highly desirable. Experience with computational methods such as density functional theory calculations, geometry optimization, and prediction of NMR parameters will be considered an advantage
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, conducting simulations and comparative performance evaluations, designing and running user studies, maintaining high-quality code and data artifacts, and preparing research outputs for publication and
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central role in supporting research design, algorithmic development, data analysis, and coding tasks across CTED’s interdisciplinary projects. Working under the direction of the Principal Investigator (PI
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, robotics, etc. is a plus. Other preferred qualifications include: expertise in programming and coding (preferably using Python and C++) and GUI development; expertise in computational mechanics and finite
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calculations, geometry optimization, and prediction of NMR parameters will be considered an advantage. The candidate should have excellent written and oral communication skills, strong organizational ability