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will be tailored to your expertise, spanning from hardware design to system-level optimization and control methods. For the AI position, you will develop machine learning models that incorporate physical
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release on these projects can be found at the following link . This position’s focus is on developing engineered systems and methods to quantify the physical interactions between migrating cancer cells and
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a project to generate knowledge and impact towards sustainable urban futures. We expect such project will mobilize theories, tools and methods of participatory design and futures studies and can be
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in the development and application of process control methods related to industrial chemical processes. We expect you to establish a high-level research group in process control, process identification
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emphasis on research infrastructure and technology rather than preparation for an academic career path. You will be involved in research, but more focused on learning and improving how computing, workflows
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Devices (QCD) group at the Department of Applied Physics. In this position you have a chance to make history by demonstrating some of the first experiments of the future quantum-computer technology that is
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first experiments of the future quantum-computer technology that is orders of magnitude more efficient than existing quantum processors. Join us in shaping the future! As a result of five ERC grants
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of an AI assistance system for fieldworkers, with a focus on large language model-based solutions for context-aware instruction generation. Your network and team The mobile cloud computing group
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batteries Conduct preliminary sustainability analyses to evaluate the environmental consequences of the chosen materials and fabrication methods Evaluate the long-term ecological responsibility
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. The experimental data obtained from Mckenna burner, optical spray and combustion chamber, and optical engine will provide valuable benchmarks for validating Computational Fluid Dynamics (CFD) models of high-pressure