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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 7 days ago
geometric transformer model to predict protein binding interfaces in flexible and disordered regions. Cell Systems, 10.1016/j.cels.2025.101454 The PhD candidate will: Curate and analyze large-scale datasets
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is to design a data architecture capable of harmonising sensor data and integrating them with artificial intelligence algorithms for predictive irrigation management. The research will include
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that help determine when an AI model is ready for use and when more research is needed. PhD in Epidemiology on value-of-information from validating clinical prediction models and AI Our goal: Develop value
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provide detailed information on local deformation mechanisms at the microscale, while numerical simulations and data-driven approaches will enable the development of predictive models capable of linking
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detailed information on local deformation mechanisms at the microscale, while numerical simulations and data-driven approaches will enable the development of predictive models capable of linking
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challenge is therefore to develop efficient surrogate models capable of rapidly predicting macroscopic mechanical properties directly from microstructural descriptors while preserving the underlying physical
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mangament in numerical models, including advanced calibration strategies from data (observations, measurements, other model predictions) and uncertainty reduction. Scientific context Many engineering and
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differential equation models of bacterial persistence. A particular challenge, both for simulation and for machine learning, lies in the high dimensionality of these equations, which causes grid-based numerical
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challenge is therefore to develop efficient surrogate models capable of rapidly predicting macroscopic mechanical properties directly from microstructural descriptors while preserving the underlying physical
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Water consumption under various application parameters Impact of dosing changes on crop quality Economic efficiency Impact on variability of soil properties Predictions based on AI models Supervisor