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. Advance Bayesian and ensemble learning approaches for non-stationary temporal processes. Implement probabilistic diffusion or generative models for long-term forecasting. Collaborate closely with
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uncertainty from climate projections into land-use forecasts. Advance Bayesian and ensemble learning approaches for non-stationary temporal processes. Implement probabilistic diffusion or generative models
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The objective of this postdoctoral position, in
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associated with phenotypic (biomechanical and metabolomics) traits. Estimate locus-specific effect sizes and quantifying genetically-driven phenotypic variations. Develop Bayesian models and/or deep learning
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                National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 2 hours ago
process in a more systematic way. Science systems engineering focuses on ensuring alignment between the design and operation of an engineered system and its top-level science objectives, but there has not
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) for engineering systems and structures, as well as expertise in machine learning, stochastic modeling, and Bayesian statistics. Programming Skills: Proficiency in programming languages such as Python, C, or R
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, stochastic modeling, and Bayesian statistics. Programming Skills: Proficiency in programming languages such as Python, C, or R. Teamwork and Responsibility: Ability to work effectively within a project team
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strategies to mitigate impacts on adjacent waters. Research activities include: coordinating with multiple stakeholders and collaborators to define objectives and research questions; leading participatory co
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, rental platforms, and production systems—where decision-making must balance conflicting objectives, leverage real-time data, and ultimately support sustainable profitability. Examples include optimizing
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tasks require high-frequency evaluations of forward models, in order to quantify the uncertainties of rock and fluid properties in the subsurface formations. Therefore, the objectives of this research