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supervised by experts in combinatorial optimization, machine learning and fairness-awareness in algorithmic decision support, and the Eurotransplant headquarters in Leiden, where access to the domain expertise
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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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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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/GPUs. These devices provide massive spatial parallelism and are well-suited for dataflow programming paradigms. However, optimizing and porting code efficiently to these architectures remains a key
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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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candidate will be an integral part of the prestigious ERC Consolidator Grant, THERMODON on harnessing the unique capabilities of ONNs to solve combinatorial optimization problems. ONNs, inspired by
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. Process simulation software is being developed for virtual optimization of tool design and material handling, enabling first-time-right manufacturing. The predictive quality of these tools relies
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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