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Field
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limited, noisy, and low-resolution measurement data? In this project, you will develop a novel physics-informed machine learning approach that integrates physical simulations of the measurement process with
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modeling, construction of numerical methods, coding, testing, numerical simulations, and possibly measurements. You will mainly do your programming work in a mixed programming environment, i.e. combining
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Polytechnique de Toulouse (INPT). The PhD student will be part of a group of largely modelling PhD students all trying to make computational fluid dynamics modelling more sustainable in a comprehensive sense
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Are you fascinated by the quantum dynamics of electrons? Do you want to contribute to the development of a novel theoretical framework for accurately simulating how electrons respond to external
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Particle Motion. The project includes nanoswitch design, sensor fabrication, sensor testing, and modelling. The longterm goal is to enable multiplexed continuous real-time sensing for applications in
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of these sensors. - Access to the laboratory's experimental characterization facilities. - A collaborative and multidisciplinary environment at the interface of theory, modeling, and experimentation. Scientific
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tasks: 1) state of the art of the face finite element modeling, 2) a patient-specific Face Modeling derived from MRI, 3) implementation of multiscale behavior of soft tissue and muscle 4) simulation
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. To fill-in this gap, you will use hierarchical molecular simulations to produce high quality thermodynamic, transport, and kinetic data that can be used for multiscale model development. We will focus both
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, system engineers and AI researchers, with access to state-of-the-art simulation tools, design software, and prototyping infrastructure. You will join the Brussels Photonics (B-PHOT) large research group
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systems. Preparation and generation of training datasets based on experimental and simulated Q-OCT data. Development of automated methods for generating training data from experimentally acquired joint