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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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hydrodynamics and/or N-body simulations in the star and planet formation context Experience in the field with HPC system usage and parallel/distributed computing Knowledge in GPU-based programming would be
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enhance human-computer interaction and improve our understanding of multimodal communication. To do so, you will have full access to motion-capture and virtual-reality labs, 3D animation tools, and GPU
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, and progression outcomes) and high-end compute (hundreds of NVIDIA H100 GPUs) via Mila and the Digital Research Alliance of Canada, and involves active collaborations with Stanford, Oxford, Google
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and tool-using agents for experiment design, simulation steering, data collection, and lab/compute orchestration; planning and memory; multi-agent collaboration. Scientific Reasoning: Program/path
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modeling, or ordinary/stochastic differential equations. Experience in computational, statistical, or machine learning method development in any discipline. Experience in GPU computing frameworks (e.g
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. Due to the interdisciplinary nature of the work, we are looking for a person with a background in performance engineering and high-performance computing hardware (high-performance CPUs and GPUs) as well
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finite elements) as well as alternative discretization methods (e.g., Lattice Boltzmann Methods), and high-performance computing. A selection of possible research areas can be found on our website: https
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, Japan [map ] Subject Areas: Mathematical and Information Science Computational Science Biology Chemistry Engineering (more...) Physics Interdisciplinary Medical Science Appl Deadline: (posted 2025/10/01
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RTDS. Experience with software development. Experience with use of GPUs, multi-core CPUs, advanced computing (e.g., QPUs). Excellent written and oral communication skills. Motivated self-starter with