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preclinical animal models required for research projects. Collaborate within interdisciplinary teams to analyze data, publish findings and contribute to clinically relevant innovations. Required Qualifications
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logging into their existing Workday employee account. Position Summary: The Postdoctoral Fellow will conduct coupled physical-biogeochemical modeling to understand harmful algal blooms (HABs) in subtropical
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Help build the model library at the heart of UTOPYS, a new national facility for real-time power system simulations. Job description Future power systems are converter-dominated, fast, and
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, to develop solutions for predicting risk in international-scale financial markets. The project is developing event-triggered artificial intelligence approaches that complement existing financial risk models
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California State University, San Bernardino | San Bernardino, California | United States | about 23 hours ago
advanced AI/LLM technologies. The ideal student will have basic experience in the following: programming skills, AI/LLM models, and data analysis and visualization. Responsibilities include but not limited
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around the modelling protocol: diagnostic checks of scenario submissions against the protocol, and documentation of harmonized assumptions and remaining differences across models Contribute to / develop
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on understanding mechanisms underlying cardiovascular disease, particularly in the context of inflammation, infection and vascular pathology, and on developing advanced experimental models to investigate
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including neuronal spiking, local field potentials, EEG, behavior, and circuit perturbations. The goal is not merely to fit models to neural data, but to develop mechanistic frameworks that generate
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areas for offshore windfarm development from Clew Bay to the north coast of the island of Ireland to the northern Irish Sea. Building on a model for NW Ireland, the researcher will collate all available
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, to develop solutions for predicting risk in international-scale financial markets. The project is developing event-triggered artificial intelligence approaches that complement existing financial risk models