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(NSSD). In this role, you will conduct fundamental research into the integration of Bayesian methodologies with system dynamics modeling, advancing statistical methods and the open-source scientific
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various application methods throughout the laboratory. Major Duties/Responsibilities: Perform all types of painting, priming, and removal on the following surfaces: interior and exterior rooms,equipment
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data and develop data-driven methods for predicting land loss and ecosystem transitions in wetland-rich landscapes of the Gulf Coast with a focus on coastal Louisiana. This candidate will directly
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, qualification, and deployment of AI agents and models, Computational Fluid Dynamics (CFD) simulation codes, and Finite Element Method (FEM) based tools for nuclear energy (fission and fusion) applications
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technical, project, operations, project controls, and finance teams, the Radioisotope Projects Integration Manager establishes and improves management methods and portfolio-wide guidelines; coordinates
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controls methods to manufacturing processes and/or manufacturing-related automation Expertise in machine learning for both sensor processing and control, including reinforcement learning and machine vision
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that have applications in multiple sectors of importance in the Department of Energy. The primary focus will be developing separation methods using mass spectrometry including microfluidics, MEMS, and mass
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quantum simulations of materials or chemical physics methods, in particular ab initio and AI-driven simulation methods Experience in statistical mechanical theory to analyze the simulation results Basic
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performance and detect anomalies Develop AI-driven predictive maintenance strategies to anticipate system failures or performance degradation Use AI/ML methods to optimize thermal system design parameters and
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, and benchmarking methods that make agentic and traditional workflows reliable at scale. The group’s main objective is to empower scientists and researchers by enabling them to effectively apply