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, health and environmental stimuli jointly determine how animals function, adapt and contribute to ecosystems. PhD: Development of AI Models for prediction of resilience and susceptibility infectious
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(DERs), PV, BESS, diesel gensets, or DC microgrids is highly advantageous. Familiarity with energy management systems, microgrid control strategies, or predictive/dynamic control will be an advantage
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for Predictive Product Properties (MTV)". Your research focuses on the experimental and material-modelling foundations required to enable predictive and controlled TVAM. You will be embedded in the Processing
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of research this position is engaged in: The Bowen lab leverages wide-scale neural recordings, predictive modeling, and continuous glucose monitoring with the goal of building foundational integrated (“multi
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integrating modeling, machine learning (ML), and advanced control methodologies. The research will focus on designing AI-driven algorithms to assess battery health, predict degradation trends, and optimize
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 1 month ago
control, and coronagraph system modeling. Location: Ames Research Center Moffet Field, California Field of Science:Planetary Science Advisors: Natasha Batalha natasha.e.batalha@nasa.gov 650-604-2813 Ruslan
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the Sustainability Institute at University College Cork. UCC invites applications for a Postdoctoral Researcher specialising in industrial decarbonisation modelling to support the EU-funded FLARE project. The role
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, prior distributions and posterior predictive checks, model comparison, programming in R (python/Matlab), implementations using R-packages rstan/JAGS and brms/STAN or equivalent interfaces. References
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understanding of ML approaches for classification, anomaly detection, and prediction using high-frequency data. Experience with multilevel longitudinal data, missing data strategies, and clinical outcome modeling
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polygenic risk scores, rare variant burden scores, and integrative prediction models. Evaluate model performance and clinical utility. Identify therapeutic targets and causal risk factors for cardiovascular