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porous materials Develop novel machine learning model for predicting gas adsorption behavior Investigate molecular transport and separation mechanisms for membrane process Publish journal articles and
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of the fluids under consideration. This will be coupled with the use of in-house models that can be employed to explore and predict the behaviour of newly developed fluids in different components and applications
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extent the research to prediction models and different product development, which can be tested on pilot scale as well. Duties As a Ph.D. student you are expected to perform both experimental and
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are considered the largest source of uncertainty in climate predictions because it is complicated to accurately model the small-scale process (microphysics) inside clouds occurring in a range from meters to
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Your Job: We are looking for a PhD student to contribute to the development of fast, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular
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. Generate, curate, and augment training datasets using FEFF-based simulations and experimental data. Conduct beamline experiments to validate model predictions and integrate them into real-time analysis
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SFI FAST: PhD position in Microstructure/texture evolution during extrusion of scrap-based Aluminium
physics- and data-driven models that deal with microstructure/texture evolution during extrusion to predict material properties of extruded profiles Collaborate with other researchers and industry partners
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topics: a) introduction of highly efficient DGL models to reduce the energy impact and increase the sustainability of DGL models; b) increase the expressiveness of DGL models, obtaining better predictive
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at unprecedented resolution. The core innovation of your work will be integrating this data to train deep learning models that predict chromatin accessibility and gene expression patterns. These models will
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Research Infrastructure? No Offer Description Mission: Support the design, training and validation of temporal models aimed at detecting ecological patterns and predicting events such as the bloom of Oceanic