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. Demonstrated expertise in using machine learning and optimization frameworks in conjunction with FE simulations to assist with component and/or process design is preferred. Excellent written and oral
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CPU and GPU based HPC systems. Exploration of the capabilities of DPU/IPU SmartNICs to support network security isolation, platform level root-of-trust, and secure platform management/partitioning
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well as dynamic and transient inverter modeling and different applications of the simulation. Selection will be based on qualifications, relevant experience, skills, and education. You should be highly self
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hardware. As part of our team, you will perform research to develop new scalable quantum simulation algorithms, based on multi-linear representation theory, and apply them to real world applications spanning
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computational thermodynamic (CALPHAD) software, such as Thermo-Calc, DICTRA, PANDAT, or FactSage. Proficiency in materials data analytics, including correlation analysis and machine learning techniques. Preferred
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priorities. Willingness and ability to learn new research areas and contribute effectively with initiative and enthusiasm. Excellent written and verbal communication skills, with a demonstrated record of
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in multiscale and multifidelity simulation techniques (ab initio methods at different fidelity, machine learning tight-binding, machine learning force fields, phase-field modeling, and/or kinetic monte
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
ML concepts and architectures and hands-on experience with open-source AI/ML packages (such as pytorch, scikit-learn, tensorflow, JAX etc.). Preferred Qualifications: Good grasp of concepts in solid