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Intelligence algorithms for the fashion industry, including predictive models for sales and trend forecasting, multimodal generative models for visual and textual content analysis, and decision-support systems
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2 Apr 2026 Job Information Organisation/Company Università di Pisa - Dipartimento di Ingegneria dell'Informazione Research Field Engineering Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Application Deadline 2 May...
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This PhD project focuses on the design and evaluation of hybrid quantum–classical algorithms for large-scale data analytics and optimisation problems. The research will investigate how quantum
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the assignment is aligned with the objectives of the SAFER project, which aims to develop algorithms for the management of mechatronics intelligent drug-delivery systems, with particular attention to the energy
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RAP opportunity at National Institute of Standards and Technology NIST Algorithms for Compound Identification by Mass Spectrometry Location Material Measurement Laboratory, Biomolecular
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electroacoustic musical composition, generative algorithmic models and computational complexity” is designed to provide students with advanced and interdisciplinary training, integrating music theory, composition
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sciences, field of information science for the group of subjects related to data structures and algorithms at the Department of theoretical and applied foundations of information sciences Where to apply E
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description: Reference No. QM 2025/16 The Research Group Theory of Electron Dynamics and Spectroscopy is looking for Postdoc / Scientist (f/m/d) for the Development of Quantum Algorithms to Simulate Electron
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guarantees of FL. In this project, we aim at an ambitious goal - designing secure and privacy-enhancing algorithms and framework for FL and applying our designs into real-world applications. To achieve
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algorithms for problems related to information markets involving multiple rational autonomous agents. The objectives include: the development of learning algorithms; the study of their theoretical properties