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Field
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through a model-driven approach, i.e. a combination of simulation- and data-driven methods and tools with data analysis and machine learning as an important part. The work builds on established theories and
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Machine Shop at the University of Utah. Learn more about the great benefits of working for University of Utah: benefits.utah.edu Responsibilities Research, design, develop, and evaluate mechanical
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various research project needs including prototype testing, feasibility assessments, troubleshooting, and evaluating/modifying designs Electrical and machine shop management (20%) • Keeping research
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of the recruitment and description of the project] * Background of the recruitment and description of the project This recruitment aims to strengthen research that, against the backdrop of advances in AI, machine
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to ETH's central compute and the Alps supercomputer at CSCS A multidisciplinary team of mechanical engineers, materials scientists, biologists, and machine learning researchers, embedded in the broader
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; data assimilation; scientific machine learning and AI applied to wildfire prediction; smoke and fire-atmosphere interactions; and experimental or observational approaches supporting wildfire model
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, materials scientists, biologists, and machine learning researchers, embedded in the broader robotics ecosystem at ETH Zurich Strong ties to industry and to our spin-offs, and support for turning your research
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in design and development of mechanical components using SolidWorks computer-aided design (CAD) tools. Experience interfacing with vendors and machine shops to procure mechanical components. Experience
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and assessing weld quality of mechanical parts in real-time by developing machine learning models that use sensor data and other tasks that are assigned to you. Core Responsibilities: Understanding
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fluid simulation and molecular dynamics simulation while strengthening next-generation simulation science that spans both fields, in response to advances in AI, machine learning, and high-performance