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- progetto FLINT, CUP B69J25001080005
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This research aims to design a sustainable framework for optimizing distributed computing systems to enhance performance while minimizing energy consumption. Existing scheduling algorithms often
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Science: Concepts and Algorithms INSY 674 075 Fridays 08:35 - 9:55 Start Date: August 31, 2026 End Date: December 4, 2026 CL Credits: 1.5 Number of Class Hours: 19.5 Remuneration: $5,912.00 Deadline
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Science: Concepts and Algorithms INSY 674 076 Fridays 14:35 - 15:55 Start Date: August 31, 2026 End Date: December 4, 2026 CL Credits: 1.5 Number of Class Hours: 19.5 Remuneration: $5,912.00 Deadline
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of the CEFE in community ecology and species distribution models with that of IMAG in probability, statistical learning, and model validation. This project falls within the scope of statistical artificial
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systems. Specifically, the research will propose an integrated framework that will couple two core components: 1) advanced algorithms to optimise participation of HPPs, or more generally of VPPs integrating
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estimation, confidence calibration, model routing, token selection, early exiting, adaptive visual processing, and efficient use of multiple foundation models. The work will combine algorithm development with
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will work closely with interdisciplinary researchers and engineers to develop novel AI algorithms, publish in top-tier venues, and translate research innovations into real-world sustainability solutions
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implementation novel machine learning and large language model (LLM) algorithms for Green AI applications. Support the research of efficient AI techniques, including model optimization, parameter-efficient fine
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research project on the optimal energy storage control under distribution system constraints. You are passionate about applying cutting-edge information technology to solve the energy and climate crisis and
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causal inference in heterogeneous data environments, addressing the challenge of enabling trustworthy causal analysis across distributed datasets while preserving privacy. The successful candidate will be