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, and c) predicting new phenomena and discovering improved materials for applications. My efforts in this area use a variety of modeling approaches to answer questions on materials systems of interest
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Your Job: We are looking for a PhD student to develop learning-based surrogate models for predicting stress fields in patient-specific arteries. Especially high stresses in plaque can lead to
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French National Research Institute for Agriculture, Food, and the Environment (INRAE) | Villenave d Ornon, Aquitaine | France | 8 days ago
be to develop predictive models dedicated to the ecological transition of agriculture. The project extends the understanding of links between metabolism programming and trade-offs with plant
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predictive models for drug response. Furthermore, we work on creating new treatment stratification methods to personalize treatment for individual patients. More information about the lab can be found here
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of pharmaceutical formulation and manufacturing processes. The role The post holder will develop and implement mechanistic models to analyse and predict the behaviour of pharmaceutical processes. Your work will
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, assess the health state of systems, and predict their future evolution and remaining useful life. The proposed approach integrates physics-based and data-driven modeling techniques, including machine
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. Combining AI-based prediction (e.g., TCNN, LSTM, etc) with musculoskeletal models to estimate and predict muscle activation and tendon force over short horizons (e.g. ~200 ms). Integrating these predictions
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policy. Dr. Kang’s research laboratory is focused in personalized testing pathways, translation of diagnostic innovations, and cancer screening. We develop predictive models, simulation frameworks, and AI
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learning models to predict ion-exchange isotherm parametersIntegration of predicted parameters into the CADET chromatography simulation framework Simulation and analysis of batch and gradient elution
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perturbations. The numerical predictions will be systematically compared with available experimental data from IRPHE to assess accuracy and refine the model, ultimately leading to a validated numerical tool