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algorithms for information gathering problems involving one or more rational autonomous agents. The objectives include: the development of learning algorithms; the study of their theoretical properties
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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
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collaborative research projects, develop novel computational algorithms, and contribute to high-quality publication and grant-related activities. The position offers opportunities to work in a dynamic research
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); Optical system analysis and simulation; Developing AI/ML algorithms; Perceptual and objective visual quality assessment for holograms. For this function, our Brussels Humanities, Sciences & Engineering
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reinforcement learning methods can be used to solve multiobjective discrete and combinatorial optimization problems. The goal is to develop new algorithmic approaches that combine ideas from machine learning
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explore unconventional ideas, develop computer algorithms for data analysis, create new experimental approaches, and apply the technique in areas like biomedicine, materials science, and geology. My group
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is recruiting a large multi-disciplinary team of postdoctoral researchers for the development of advanced computational imaging techniques and their cutting-edge applications in radio astronomy, space
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Tiny Machine Learning (TinyML). The role will focus on the design and development of battery‑less, ultra‑low‑power IoT systems capable of executing secure TinyML‑based visual perception algorithms
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Federated learning (FL) is an emerging machine learning paradium to enable distributed clients (e.g., mobile devices) to jointly train a machine learning model without pooling their raw data into a
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advanced machine learning models and physics-informed algorithms for analyzing high-speed XRD data, with a focus on identifying critical transformation windows and assessing phase evolution kinetics