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neuroimaging data constrained by patient's structural connectivity and tractography • Using the results of the TVB model fits to stratify patients and predict disease progression • Organizing and unifying
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selectivity and permeability and ultrahigh water permeability combined with high salt rejection. The objective of this work is to construct atomistic models of MOFs/Polymers and Artificial Water-Channel
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experimental design. Deep expertise in predictive modeling, classical ML algorithms (e.g., decision trees, gradient boosting), large language models (LLMs), generative AI, MLOps, and AutoML using frameworks like
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of atmospheric dynamics, climate and weather prediction models and earth system modelling), and Space Sciences (meteoroid modelling and composition, atmosphere-meteoroid interaction and cosmic dust) Knowledge in
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quantitative predictions testable against empirical data from diverse ecological contexts. We use methods from theoretical evolutionary biology, including optimal control theory, life history modelling, adaptive
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to combine high-throughput metabolomics with 3D cell culture models Perform large chemical and genetic studies in cancer cell lines derived spheroids Develop predictive model of drug response by comparing 2D
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a passionate community collectively aiming to bring novel technologies and science to cutting-edge numerical weather prediction. ECMWF has been the first operational weather centre globally to
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Monitoring Duties & Responsibilities: Build early warning and clinical deterioration prediction models Develop continuous clinical risk trajectory modeling frameworks Model time-series data such as vitals
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technology. Development of cutting edge foundation models for protein design, small molecule property prediction, or protein function prediction Data generation and curation, including molecular simulation and
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
research on the integration of Digital Twins with AI/ML technologies for infrastructure lifecycle management. Develop and validate computational models for monitoring and predicting infrastructure