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the display and the distribution of processed data. Related projects and responsibilities will include: Creation of artificial intelligence algorithms that effectively integrate molecular, pathology/image, and
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progress. Ability and willingness to work some flexible hours. Extensive experience in large-scale pre-training of large language model. Experienced in developing machine learning algorithms and large
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to machine learning algorithms in order to get uncertainty estimates for parameters governing the distribution of the observed data. The predictive Bayes scheme for uncertainty quantification contains a wide
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international collaborators across clinical, academic, and industry settings to develop privacy-preserving machine learning approaches, federated learning frameworks, and interpretable algorithms for multimodal
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quantification, in particular the theory and methods known as predictive Bayes. Predictive Bayes theory involves getting Bayesian type uncertainty for parameters given data (i.e., a posterior type distribution
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algorithms for parallel/distributed AI/ML Hardware-aware and resource-efficient partitioning for parallel/distributed AI/ML Optimization of process-to-process communication in parallel/distributed AI/ML
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National Lab, University of Tokyo etc.), the PhD candidate is expected to research on some of the following themes: New algorithms for parallel/distributed AI/ML Hardware-aware and resource-efficient
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prototypes. Signal Acquisition & Processing Develop acquisition pipelines to capture vascular motion during CPR. Implement signal‑processing algorithms to extract markers of blood flow. Model Development
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distributed energy resources (DERs). Design & develop optimization algorithms/tools to plan the deployment of DERs such as energy storage systems (ESS), photovoltaic generations (PV), electric vehicle charging
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inclusive place to study and work. Postdoctoral Research Fellow position within acoustics and distributed fibre optic sensing At the Department of Physics and Technology , there is a vacancy for a