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Field
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to staff position within a Research Infrastructure? No Offer Description CIATec selects 1 FAPESP Postdoctoral Fellow to work on the development of predictive models and recommendation systems, based
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-based models as well as patient-derived xenograft models of liver cancer. This position is suitable for a highly motivated self-starter who excels in a dynamic environment offering varied learning
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simulation, including O/D modeling, multimodal network modeling, agent-based or behavioral modeling Large-scale computing, cloud-native analytics workflows, and data engineering for mobility platforms AI/ML
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pipeline for predicting human pathogenicity based on bacterial genomes, something that has recently been expanded using more novel AI-techniques. There is, however, a need to further expand this to also
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reinforcement learning Experience with high-performance computing, physics-based simulations, and multimodal data workflows Demonstrated ability to train and deploy AI/ML models using simulated and experimental
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supervision of PI Calina Copos and will engage in collaborative work with cell and developmental biologists. Expertise in agent-based models, continuum PDE descriptions, dynamical systems, and/or ML-based
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description] Research on the development of cognitive models for nonverbal communication channels between AI agents, as well as duties related to the research project. * Assigned department Existing departments
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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
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integrated assessment modeling, energy system modeling, or agent-based modeling, who are eager to incorporate socio-political dynamics into their models; or 2.Computational social scientists with experience in
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sparse-regression based techniques to derive interpretable and computationally efficient differential equation models from computationally intensive multi-cellular agent based models (ABMs) of Epstein–Barr