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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 21 hours ago
with experience in causal inference predictive modeling, and data linkages will be given preference. Preferred candidates will have a strong publication record for their career stage, strong oral and
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) Develop AI‑driven model calibration by designing a deep‑learning pipeline mapping data extracted from experiments onto force fields and use these predictions to initialise Cytosim simulations. (3) Use
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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | about 2 hours ago
system. Climate models are important tools for improving our understanding and prediction of atmosphere, ocean, and climate behavior. We seek candidates with an interest in advancement of radiative
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cortex, analyze neuronal population data, and build generative or predictive models to simulate cortical responses. The position requires strong experimental engagement and a collaborative mindset within a
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. The postdoctoral scholar will contribute to an exciting research program within the Foy Lab (https://foylab.xyz/ ), focused on developing computational methods to enhance how we collect, analyze and use clinical
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methods for prediction, prevention, diagnostics and treatment of diseases. Job description This research project aims to understand how different yeast species sense, uptake, and metabolize lactose, and how
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, and process modelling. The position is available immediately, with a start date as soon as possible. Where to apply Website https://www.academictransfer.com/en/jobs/357300/postdoc-position-in-microbial
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well as upscaling to larger areas and model-based predictions for the future. In this project, the Chair of Forest Sites and Hydrology at the Institute of Soil Science and Site Ecology offers, subject to the
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. Our dedicated and compassionate faculty and staff are driven by a common mission: Contribute to innovative approaches in predicting, preventing, and curing diseases, shaping the future of medicine
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. The work is part of the regional project “Optimizing Renewable Energy Integration: FPGA-Based Model Predictive Control (MPC) for Grid Stability” (Ref. SI4/PJI/2024-00238), funded by Comunidad de Madrid and