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. Specific responsibilities include, but are not limited to, the following: Develop the core tensor network algorithm for full RIXS cross-section simulations. Benchmark simulation results against ED codes
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• Proficiency in scientific programming, preferably Python or C/C++ • Strong written and oral communication skills Desired Qualifications: • Familiar with mathematical and coding aspects of neural networks
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neural networks (CNNs) for extracting features from full-field atmospheric data Demonstrated experience coding in Python Experience modeling unsteady wind loads from atmospheric flows Experience in flight
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multi-omic sequencing, network biology, and machine learning to identify actionable biomarkers and therapeutic vulnerabilities. The successful candidate will work at the interface of computational
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Level Pro FLSA Code Administrative Patient Sensitive Job Code? No Standard Hours per Week 40 Full Time or Part Time? Full Time Shift Day Work Schedule Summary VP Area U of U Health - Academics Department
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cleaning of the meditation RCTs, including coding of PICOs and effect sizes; (b) collaborate with Dr. Sun and other members of the lab to conduct meta-analysis and network meta-analysis based on priority
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 2 months ago
Organization National Aeronautics and Space Administration (NASA) Reference Code 0202-NPP-MAR26-JPL-HelioSci How to Apply All applications must be submitted in Zintellect Please visit the NASA
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Previous Job Job Title Post-Doctoral Associate - SME Next Job Apply for Job Job ID 372823 Location Twin Cities Job Family Academic Full/Part Time Full-Time Regular/Temporary Regular Job Code 9546
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. Experience in numerical methods and CFD development using mesh-based scientific codes. Expertise in the lattice Boltzmann method (LBM) as evidenced by their publications High performance computing (HPC
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classes and their roles in scientific applications, such as deep neural networks (DNNs), convolutional neural networks (CNNs), transformer models, and graph-based neural networks. Familiarity with software