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of data analytics and mathematical modeling to predict clinically relevant biological outcomes using in vitro engineered tissue systems and in vivo models and will play a central role in the development
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teams. Unit URL https://imci.uidaho.edu/ Position Qualifications Required Experience Experience with statistical or predictive modeling as demonstrated by publications in the field Evidence of strong
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SyMulDaM project involving the development of predictive models to quantify the integrity and durability of a nuclear power plant containment structure., within the mechanical engineering department
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . The research associate will focus on Vision-Language Model based situation awareness and decision-making
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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 | 12 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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incorporate clinical, lifestyle, and nutritional factors to build predictive models through advanced bioinformatics and machine learning. By identifying molecular signatures that distinguish responders from non
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computational physics and/or geosciences and a strong interest in machine learning, Earth observation, and numerical modelling for Arctic prediction. The PhD project will develop methods to improve monitoring and
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from semantic radio maps; learn which features act as reliable predictors of rewards or outcomes; associate these features with predictive models that guide decision-making; exploit such cue–outcome
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Details The aim of this project is to combine nanomechanical methods with modelling (i) to develop quantitative, predictive models for the behaviour of molecules in sliding contacts, and (ii) to understand