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mining waste deposits (MATs). This project integrates mineralogical and mechanical characterization, pilot-scale testing, and advanced process simulation, with the objective of optimizing grinding
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transformer-based architectures to create a powerful tool for understanding and predicting bacterial genomic sequences. The successful candidate will play a key role in developing and optimizing these models
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is expected that they will actively and creatively develop and optimize the detailed methods to pursue the overall project goals and, after a training period, independently analyze genomic data using
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for these polymers and implement computational algorithms to assist their optimization. The RISE Polymer Lab is dedicated to developing the next generation of robust, intelligent, sustainable, and evolving (RISE
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dedicated to advancements in sustainable energy through innovative research and training. Our focus lies in the design, development, and optimization of inorganic materials for various sustainable energy
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di Cuneo) will focus on: Sharing French and Italian experiences and jointly reflecting on the optimal placement of new measurement and observation instruments to be deployed during the project; Pooling
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, analysis, and optimization. The goal of the project is to develop methods for the synthesis and analysis of systems producing renewable fuels and chemicals; and use these methods, in collaboration with other
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uncertainty quantification into scientific machine learning workflows and optimize the design of computational (ABM) and wet-lab experiments. • Collaborate with mathematical modelers and experimentalists in
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. This position offers an exciting opportunity to work at the intersection of HPC and AI, addressing critical communication bottlenecks and optimizing network interconnects for large-scale distributed systems
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in Kenya. The insights gained from your research will contribute directly to optimizing the deployment of spatial repellents to reduce malaria transmission. You will be part of a diverse and