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well as next-generation ecological models that take uncertainty into account. The https://leca.osug.fr (LECA) is part of the University of Grenoble Alpes and the CNRS in France. Grenoble is located close to
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, development, and evaluation of a digital twin model for on-site, renewable-driven green hydrogen generation systems. The successful candidate will contribute to an industry-sponsored applied research project
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position in the area of Learning, Optimization, and Decision Analytics. SCAI (https://scai.engineering.asu.edu/ ), one of the eight Fulton Schools, houses a vibrant Industrial Engineering and Computer
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believe that generative pre-training offers a promising path to a new class of models that work across settings and can support prediction of many different clinical outcomes at once. To fuel your models
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comfort throughout the year in a Nordic climate? Is it possible to predict dynamic outdoor thermal comfort with sufficient accuracy using fast parametric algorithms and machine learning (ML) models instead
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supports tasks such as predictive modeling, anomaly detection, and synthetic data generation. The models developed are expected to exploit metadata to guide and condition image analysis outputs. By
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derived spheroids Develop predictive model of drug response by comparing 2D to 3D cellular systems Testing and validating the relevance of such models in patient tumour specimens Support and preparation
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of effluents (collaboration with wastewater treatment plants and industries). Analytical monitoring (HPLC, LC-MS, spectrofluorimetry, toxicity tests). Modeling: Development of predictive models for process
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wide variety of translational neuroscience research programmes. The focus of the role will be analysis of large clinical datasets from PRECISION-ALS (n~20,000) and PRO-ACE to develop prediction models
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understanding of the underlying physical mechanisms and to leverage this knowledge to develop predictive tools for optimizing the design and control of wind farms. Research scope and responsibilities Depending