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motivated and curious candidate with a background in computer engineering, embedded systems, or a closely related field. The ideal candidate has an interest in the intersection of artificial intelligence
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on numerical simulation of the turbulent urban boundary layer using the transient mesoscale model PALM‑4U. The work involves developing the model to integrate multi‑physical parameters and boundary conditions
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nanosatellite/CubeSat constellations and to develop innovative GNSS-based sensing methods and AI models to detect a variety of Earth surface processes. This PhD position focuses on developing analytical models
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already at the early design stage. In this role, you will develop power converter integration concepts that support design for disassembly. Multi-physics simulation tools will be used to analyze
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on reinforcement learning (RL) for policy discovery in a multi-sector “integrated modeling environment” that connects fast ML metamodels of simulators (e.g., transport, energy, environment, climate events). The aim
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good process simulation and sustainability assessment skills. The FrameBio PhD project, is part of prestigious Marie Skłodowska-Curie Actions (MSCA) Doctoral Network, a collaboration between 16 partners
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disassembly, reuse, and remanufacturing already at the early design stage. In this role, you will develop power converter integration concepts that support design for disassembly. Multi-physics simulation tools
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. To do so, you will combine atomistic simulations (density functional theory and ab-initio molecular dynamics simulations) with new machine learning models to parameterize machine learning force fields
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properties, e.g. high processability while maintaining an open porous structure. However, their fundamental vibrational behavior remains poorly understood. This limits the possibilities to enhance