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real-world test flights to validate system performance on an innovative VTOL platform (https://aerogriduav.com/). AI models to predict ship motion to optimize landing timing. You will work at the MAVLab
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, develop innovative therapeutic strategies, and optimize drug delivery to improve human health. Our teams combine expertise in nanomedicine, RNA biology, organoid models, and the tissue microenvironment
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/pharmaceutical-technology-and-biopharmacy/ ). Researchers at GRIP aim to understand the molecular basis of disease, develop innovative therapeutic strategies, and optimize drug delivery to improve human health
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strategies (e.g. predictive or machine learning approaches) to improve performance and reduce costs. Collaborating with industrial partners on design optimization, life-cycle analysis, and business case
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on design optimization, life-cycle analysis, and business case development. Publishing results in journals and conferences, and engaging with stakeholders through workshops and demonstrations. The position is
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issues. Thus, there is a growing demand for efficient and reliable digital CIM-based neuromorphic system design which includes techniques such as reliability-aware mapping and optimization techniques as
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, there is a growing demand for efficient and reliable memristor CIM-based neuromorphic system design which includes techniques such as reliability-aware mapping and optimization techniques as well as high
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methodologies; You will characterise the materials using spectroscopic and surface characterisation techniques; You will identify and implement optimal methods for the integration and testing of materials in real
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includes techniques such as reliability-aware mapping and optimization techniques as well as high-quality, and cost-effective mitigation schemes that can guarantee efficient and reliable operation. The
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reliability-aware mapping and optimization techniques as well as high-quality, and cost-effective mitigation schemes that can guarantee efficient and reliable memristor-based CIM operation for AI workloads