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Field
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renewable postdoctoral position is part of an innovative project focused on characterizing the modification of bio-based materials using natural enzyme mimics capable of oxidizing biomass, particularly
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Chemistry to conduct fundamental and applied research at the intersection of machine learning and computational chemistry. In this role, you will develop physics-informed, symmetry-aware models
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will support and conduct simulation modeling research related to tobacco and lung cancer prevention and control. Duties include: Conducts data analysis using secondary data sources, such as national
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) and contribute to LU-PCG’s research under the U.S. Department of Energy’s (DOE) GENESIS Mission. Research will involve developing fast neural surrogate models, state estimators/virtual sensors, multi
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experience of mixed phase numerical or analytical flow modelling / solid mechanics / material characterization. Experience of analysing experimental data is highly desirable. You should have a record of
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material, device, and process scales Plan and execute experiments to support and augment modeling efforts Conduct simulations using state-of-the-art tools to supplement model development Contribute
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to 50 lbs. Shift Monday – Friday 8:00am – 5:00pm (40 hours/week) Job Summary The postdoctoral researcher will assist the faculty PI and Co-PIs in advancing materials and manufacturing processes in
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mouse models. Experience studying the hypothalamus or neural regulation of metabolism. Experience with neural tracing techniques. Experience performing stereotaxic surgery in mice. Excellent
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cell biological and biophysical characterization of various alpha-synuclein aggregates/oligomers found in vivo (Mouse models and human tissue) that can induce neuropathology/neurodegeneration. 1
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-particle physics, predictive modeling, and AI-enabled digital twins for magnetically confined fusion plasmas in tokamaks. The research will combine high-fidelity simulations, reduced transport modeling