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Infrastructure? No Offer Description Mission: Provide support in the development of substitute models to incorporate them into musculoskeletal simulations and assist in motion capture within the framework
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the rate of fire growth. State-of-the-art fire models designed for these simulations also require input parameters (material properties) that describe: the decomposition reaction mechanism of combustible
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models (Thesis 2). In France, patients with chronic kidney disease (stages 1 to 5 or on dialysis), monitored by the Charles Mion Aider Santé Foundation across 23 centres in Occitanie, will enable the study
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computing. This particular position focuses on time-series analysis and forecasting using transformer based foundation models. About the Project Time-series prediction using transformer based models is
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applications for a unique postdoctoral position focused on the development of digital models of the human colon and surrounding organs to simulate their behaviour during colonoscopy procedures. The successful
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probes and in combination. More specifically, the project requires developing the SBI framework including simulations as forward models of observables, performing inference on synthetic datasets and
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performance. To validate the achieved tuning range and functional performance in laboratory measurements against modeling and simulation results. This position is part of the MetaTune Doctoral Network
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learning workflows, and developing complete models. Example applications include drug design, cryo-electron microscopy, structural prediction and dynamic simulation of biological macromolecules, genomics
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to mechanical stimulation Methods and Approaches: The project combines state-of-the-art experimental and computational techniques, including: Transgenic mouse models and lineage tracing Orthodontic tooth movement
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data, model-based simulation coupling, and uncertainty-aware outputs for lab/clinical validation. Work with 3D datasets, time-series sensors, and multi-omics or assay data to create predictive models and