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for vehicle applications; Abilities in using Finite Element modeling and analysis; Knowledge of injury biomechanics; Knowledge of Artificial Intelligent (AL) and Machine Learning (ML) techniques; and Abilities
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University of California, San Francisco | San Francisco, California | United States | about 10 hours ago
, including the ability to abstract information requirements from real-world processes to understand information flows in computer systems. Ability to represent relevant information in abstract models. Critical
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will have the opportunity to learn and apply advanced data analysis techniques, including machine learning and econometric modeling. Through collaboration and technical expertise, this position supports
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/Master’s degree in statistics, mathematics, computer sciences or a related field Thorough knowledge of methods in event history analysis and multi-state models is required. The candidate should be familiar
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee We are looking for a Research Assistant to carry
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simulations with machine learning models derived from experimental data. 1) Functional Knowledge and Technical Expertise (50%) a. COMSOL Modeling: Design, build, and run COMSOL Multiphysics simulations to model
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between Numerical Analysis and Machine Learning, with a focus on physics-informed machine learning. The goal is to design learning strategies that embed the structure of governing physical laws, enabling
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, or probabilistic modeling, and be proficient in Python and modern machine-learning frameworks (ideally PyTorch). Experience with single-cell transcriptomics, epigenomics, proteomics, spatial omics, or multimodal
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-fidelity finite element models to investigate surface wave propagation in soft biological tissues, forming the foundation for subsequent statistical and machine learning frameworks that integrate
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targets to treat anhedonia. Proposals that challenge prevailing assumptions, employ cutting-edge technologies, or integrate machine learning with neurobiological data are especially welcomed. Projects