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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 2 days ago
lives. The Theis Lab at the Computational Health Center is internationally recognized for pioneering methods in machine learning, single-cell analysis, and computational modeling of complex biological
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-based ecosystem modeling, MRV/CDR, nature-based solutions, or food–energy–water systems. Experience with machine learning, remote sensing, or near–real-time environmental data systems. Experience
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predictive modelling; Bioinformatics and Knowledge Graphs (visualization and reporting); AI-based data integration across cohorts (with federated machine learning); Contribute to ongoing projects, such as: o
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, computational biology, or bioinformatics with a heavy focus on machine learning and AI model training and development by the appointment start date. About 1 year of research or work experience in an academic
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) data. We also analyse macaque electrophysiology data obtained through collaborations. We use machine learning techniques for data analysis and computational modelling with a special interest in
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As a component of the faculty cluster initiative, the Chancellor’s Faculty Excellence Program , NC State University is recruiting one tenure track Assistant Professor in mathematical modeling/machine
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Mobasher. It involves a diverse range of activities including: structural and geotechnical modeling, machine-learning model development, structural sensing and health monitoring, conducting physical
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learning, initiating an atmosphere of care via our caring campus model, and enrichment of the quality of life in the region it serves. Serving Martinsville, Henry County, Patrick County, and the southern
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to oversee research activities outlined in NSF Grant 2520154 “Understanding Expectation-Driven Learning in Early Childhood: An Experimental and Computational Investigation,” under the supervision of Dr. Kimele
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applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process industries; advanced process control (APC); model predictive control (MPC); digital