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Field
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the laboratory's focus on neuroimmune interactions and trauma-related physiology. Develop and implement mouse models relevant to neuroimmunology, stress biology, cardiovascular physiology, and immune-mediated
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of large-scale geospatial and time-series datasets. The candidate will develop and evaluate multimodal AI models to characterize vegetation and land-surface dynamics and quantify ecosystem responses and
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systems. In parallel, they will design and develop agentic AI and physics-aware AI models to accelerate discovery and deepen mechanistic insight in catalysis. This work will be carried out in close
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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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make a difference in the world! Position Information Texas A&M AgriLife Research at Temple is seeking a highly motivated scientist with expertise in crop modeling, remote sensing, and geospatial
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modeling approaches. The successful candidate will design and conduct experiments, develop and implement analytical and numerical modeling approaches, and perform microstructural characterization to evaluate
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), and have a valid driver’s license. Instructions To apply, candidates will submit the following materials via Interfolio: A cover letter (1-2 pages) describing research fit and relevant modeling
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experiments, and connect them into live experimental campaigns so that AI checks every candidate before it reaches the robot deployed on the Genesis American Science Cloud with the Materials Project as
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learning (ML) to address future physics and detector challenges. Current physics interests include Standard Model measurements and searches for new phenomena. We welcome applicants who are excited
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artificial intelligence. Potential research topics include the mathematical and statistical analysis of modern generative models, particularly diffusion- and flow-based models, as well as their applications