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excellence. Candidates should propose an innovative research program that fits within the global themes of the IGMM and addresses a fundamental biological question. Such a project can be positioned
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for computational efficiency, ensuring scalability to large-scale datasets, and their performance will be analyzed. The project will explore applications in smart city monitoring, an area where the team has
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; developing our partnership programme with industry; contributing to a quality management system; and the organization of webinars and other dissemination activities, including publications. Support from
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to perceive their environment because this sensor can produce precise depth measurement at a high density. LiDARs measurements are generally sparse, mainly geometric and lacks semantic information. Therefore
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objective function (eg, approximation error). A key question is to devise an algorithm that organizes the operators into a sequence, such that the best operators (low cost and high benefits) are performed
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to pilot and demonstrator levels, particularly for polymeric and functional materials. Perform key parameter calculations (e.g., heat/mass transfer, mixing, kinetics) to guide scale-up decisions. Design, set
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enabling trustworthy AI adoption through methods and tools for compliance, readiness, and performance evaluation. In the field of Smart Cities, we lead the operations of the CitCom.ai project. CitCom.ai is
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with high dimensionality: Computational difficulties linked to the high dimensionality of the underlying tensor approach have been tackled in [GOU20] by undersampling the measured AF ECG signals
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for process-local loose coupling in high-performance simulation codes. PDI supports the modularization of codes by inter-mediating data exchange between the main simulation code and independent modules (plugins