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the performance and scalability of large-scale molecular dynamics simulations (e.g. LAMMPS) using machine-learned potentials (e.g. MACE) through algorithmic improvements, code parallelization, performance analysis
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financial models. The position will include the analysis of hydropower operation and expansion, optimization and equilibrium, market penetration, and interdependencies. This description documents the general
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devices, with emphasis on lithium-ion, sodium-ion, and lead-acid battery systems. Modeling and analysis will leverage tools such as COMSOL, MATLAB, Excel, Python, and related scientific software. The role
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the following areas is highly desirable: AI/ML for predictive modeling and inverse design of nanomaterials and nanoscale systems AI-enabled analysis of experimental data (e.g., microscopy, spectroscopy
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venues Position Requirements Required skills and qualifications: A PhD degree completed within the last 0-5 years (or soon to be completed) in numerical analysis, applied mathematics, computational science
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emphasize multi-wavelength survey science, the galaxy-halo connection, cluster cosmology, and large-scale cosmological simulations. Analysis efforts cover topics such as CMB power spectra, CMB lensing, galaxy
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survey analysis Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork Preferred Qualifications Background in observational cosmology, galaxy clusters, or wide-field
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their relationship to topology in a variety of materials exhibiting out-of-plane component of magnetization. Here the target materials are those with interfacial DMI (e.g.: Co/Pt multilayers) and chiral
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applying machine learning or other elements of artificial intelligence to solving significant scientific or engineering problems Interest in software development, with particular emphasis on the Python
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on the LLM/agent and HCI layers of IDEAS, including: Mixed-initiative AI assistants for visualization and analysis, Natural interaction paradigms for scientific workflows, Integration of agentic systems with