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Field
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opens a call for the assignment of a research grant, with one position(s), under the project SOMIPs - Simulation, Optimization and Monitoring using AI-based Digital Twin Technology for Incineration Plants
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modelling and improving Earth System Modeling by better merging of measurement data and model simulations. This PhD project focuses on improving how we estimate key parameters in land-surface and ecosystem
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position will included tasks related to integration synthetic genetic engineering, time-lapse microscopy imaging, lab-on-chip technology and advanced computer model simulations -- El puesto de investigador
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Midlands Graduate School Doctoral Training Partnership | Leicester, England | United Kingdom | 3 months ago
the precise mechanisms that drive addictive behaviour. The project will combine formal modelling, experimental simulations of socioeconomic gradients, and self-reported measures of early life
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outcomes. The Postdoc Researcher will play a key role in implementing system prototypes, managing data pipelines, and supporting the development and validation of AI models in collaboration with clinicians
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validation tests. 2. Digital Modelling & Data Analysis Support development of the AI-enabled simulation and digital model platform. Run thermal–electrical models (COMSOL, ANSYS, or equivalent). Analyse field
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simulation and network-based methods for epidemiological modeling. ● Develop reinforcement learning models for decision-making during epidemic outbreaks. ● Documenting the entire process and all the codes
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to model development, experimentation, data processing, and performance evaluation as part of an active research environment. Responsibilities Implement and experiment with computer vision models using
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. The position involves close collaboration with experts in cardiovascular simulation and Scientific Machine Learning. Your tasks: Development and comparison of data driven models for the prediction of stresses in
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geometries. Current simulation-based approaches require complex 3D meshes and are often too slow for practical medical use. This project aims to create accurate and rapid surrogate models by combining physics