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as possible thereafter. The Role Drawing on over a decade of formulation data, you will develop machine learning models that link chemical composition and processing parameters to the physical and
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machine construction and/or mechatronics Experience in simulation, modelling and CAD/CAM programming Demonstrated ability to create high quality publications, reports, and potentially research proposals
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 8 hours ago
mathematical and computational models of the coupled thermo-fluid dynamics of wind and surface-wave driven shelf-water polynyas in polar oceans. As magnets for biological activity, centers for deep salty water
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) models developed within the team. LES Development & Application: Implement and extend open-source LES codes to simulate diverse ABL scenarios, including varying stability, shear, and turbulence intensities
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 29 days ago
of spin–lattice models tailored to specific classes of magnetic materials, - validation of the developed models using representative systems through atomistic simulations and spin‑dynamics calculations
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. You will develop a high-fidelity 3D model of submerged Lower Nubian villages and build a Retrieval-Augmented Generation (RAG) pipeline in Google AI Studio Pro to create voice-enabled AI agents grounded
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of oxygen and Earth’s first global glaciation about 2.4 billion years ago. Key responsibilities: design, run, and analyse equilibrium and transient simulations with a coupled Earth-system model
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at the AU Biogas facility. Conduct in-depth performance mapping including gas analysis, hydrogen yield, energy consumption, and carbon black morphology. Conduct process and plasma simulations as required
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) of the models with many competing energy scales originating from spin, charge, and orbital degrees of freedom, i.e., to investigate multi-orbital Hubbard model, generalized Kondo-Heisenberg model, spin-orbital
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work will provide the "ground truth" for the project. By simulating complex inflow conditions, you will create the high-fidelity datasets required to validate the Wind Field Forecasting (WFF) models