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Field
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pathogen genomics of a project building predictive tools for cotton soil-borne disease management. The work is supported through a cooperative agreement with USDA-ARS and is conducted in collaboration with
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Requisition Id 16704 Overview: We are seeking a Postdoctoral Research Associate who will focus on AI-enabled plant ecophysiology to improve mechanistic understanding and predictions of ecosystem
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 1 month ago
accelerate scientific discovery in strategic energy research. As a postdoctoral researcher, you will investigate rich real-time and historical operational data, to explore a predictive digital twin
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at the University of Utah (https://www.boschlab.com/) invites applications for a computational post-doctoral position to support projects related to biomolecular interaction prediction using AI tools. The Bosch Lab
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modelling; repeated-measures or longitudinal intervention data; randomized controlled trials or intervention research; open science practices. Teaching The position includes a 20% teaching obligation
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(7) Deep Learning in Biomedical Sciences (8) Theory and methods on prediction, control and estimation (9) Mathematical analysis and modeling of social behaviors where numbers (1)-(9) above correspond
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, greenhouse, controlled-environment, and field experiments evaluating seed coating integrity, delivery characteristics of plant defense signaling compounds, and interactions with seed pathogens and early-season
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or more of the following areas: Advanced Process Control and Optimization Digital Twin and Modeling & Simulation Predictive Maintenance and Fault Diagnosis Industrial IoT and Edge Computing Good programming
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the area of precision network neurology, with a focus on understanding how risk factors contribute to brain aging. This research is situated within the framework of predictive, preventive, personalized, and
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intelligence as applied to trauma systems and acute care surgery. Fellows will engage in cutting-edge research spanning multiple domains, including risk prediction models for surgical complications, clinical