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Field
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successful candidates will dedicate their efforts to the following specific research objectives: (1) Developing models for predicting the thermal runaway (TR), venting, and jet fire in a single cell with
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for structural biology. This project sits at the intersection of X-ray scattering and deep learning, aimed at integrating experimental data to predict protein ensemble structures. As an Empire AI-funded fellow
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involving use of AI in image analysis and predictive modelling Develop prediction models that can predict product yield and quality from HTP data either for cultivation management or for predicting which
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real-time field observations into process-based modeling to improve prediction accuracy. Through this educational experience, you will develop advanced skills in process-based cropping system modeling
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artificial intelligence (AI)-based tools to enable predictive modeling of biological systems. You will have the opportunity to contribute to JGI’s strategic initiatives in AI-powered functional genomics
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develop numerical models and Machine Learning and AI methodologies, including Physics Informed Neural Networks (PINNs) and Symbolic Regression tools, to predict chemical reactions, impurity evolution along
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modelling using Delt3D software. The role of the researcher is to perform physics-based modeling to build a numerical model that can predict storm surges in Singapore coastlines based on different weather
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working with numerical weather prediction (NWP) or Earth system models such as WRF or the Unified Model. Strong preference will be given to candidates with experience in next-generation frameworks like
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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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. This role is ideally suited to a researcher with experience in computational structural biology, glycobiology, or protein modelling, who is interested in applying AI-enabled structural prediction and glycan