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to train an AI model that predicts the cis-regulatory code for synthetic genomes (i.e. for cell-free gene expression systems) and correlates the experimental conditions within the synthetic cell
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Reconfigurable/Spatial computing architectures, such as FPGAs, CGRAs, and AI accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs
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fields that influence cell motility and arise in classical models of cell sheets such as the Vertex and cellular Potts models. We will specifically consider dynamic graphs that can reorganize, both
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antibiotic resistance is a major concern for both Mtb and NTM, and there is need for novel therapeutics. This PhD project investigates the potential of targeting host-cell metabolism to deprive intracellular
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Vacancies PhD position: Enabling Membrane-Based Industrial Effluent Reuse using Model Predictive Control Key takeaways The Netherlands is a water-scarce country. We therefore need to focus
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throughout the horse breeding season (March–August). Your research will bridge basic biology and translational embryology. Using live imaging and single-cell sequencing approaches, you will investigate how
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As urban populations grow and energy demands rise, urban-scale energy system modelling is critical for reducing emissions, enhancing resilience, and integrating high shares of renewable energy
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and cultural activities external link . We also offer access to additional employee benefits through our Terms of Employment Options Model. In this way, we encourage our employees to continue to invest
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are seeking a highly motivated PhD candidate to develop efficient on-device generative AI systems based on large language models (LLMs). The project focuses on creating compact, low-latency, and energy
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model of human working memory. During the project, we will follow an intertwined model-experimental approach. First, we will use electroencephalography (EEG) experiments to investigate the neural basis