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Field
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manufacturing. As steel is highly recyclable its usage helps in creating a more sustainable world. For simulations of industrial processes concerning such complex materials one must typically rely on continuum
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flow batteries (RFB), enabling affordable and durable long-duration energy storage. The approach is to use hierarchical structures, i.e. complex material layers that can be optimized to specific battery
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manufacturing. As steel is highly recyclable its usage helps in creating a more sustainable world. For simulations of industrial processes concerning such complex materials one must typically rely on continuum
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developing intelligent algorithms that can support repair and remanufacturing decisions for sustainable manufacturing? As a PhD researcher, you will create innovative machine learning solutions to optimize
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. In this PhD-project, you will propose and evaluate new AI methodology to ensure that organoid data can be used to optimally predict relevant patient outcomes. You will use a real-world case study on
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and thus go beyond relatively straightforward safety and progress properties, system requirements related to the timing of events and the results from performance optimization need to be included in
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, and engineering to optimize and upscale and biodegradable structures that temporarily mimic key emergent traits using industrial-scale additive manufacturing (i.e., 3D-printing) techniques
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industrial contexts; investigate optimal levels within the product structure for deploying AM in repair and spare parts support; integrate forward and reverse flows in manufacturing and maintenance
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organisms have been lacking. You will build on our recently developed single-cell ribosome profiling methods for C. elegans and further optimize them to apply to the early embryo. With this approach, you will
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. Specifically, the team will test a new framework that combines methods from ecology, industrial design, and engineering to optimize and upscale and biodegradable structures that temporarily mimic key emergent