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the ATLAST telescope and the nearby community of San Pedro de Atacama. The PhD candidate will have the unique opportunity to shape the renewable energy management system by developing novel real-time control
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of teaching and research, the FSTM seeks to generate and disseminate knowledge and train new generations of responsible citizens in order to better understand, explain and advance society and environment we
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networks, making use of intelligent AI-driven control planes. The work will involve: i) (i) development of network probing algorithms for OSNR/GSNR measurement automation; (ii) development of adaptive ML and
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, calibration, and the development of analysis tools and software. Our key focus areas are the physics of jets, top quarks, and EWSB, including the development of novel machine-learning methods for high-energy
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) or neural network-based methods. The level of the targeted problems will require further mathematical and algorithmic developments over the current state of data-driven SSM reduction. The PhD position will
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innovative material solutions. This project tackles this challenge head-on. The project vision is to develop a pioneering AI-driven methodology for designing Functionally Graded Materials (FGMs) specifically
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effects in economic decision-making, and other topics related to development and macroeconomic behavior. Many of these studies involve the collection of data using computational algorithms and analysis
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computational scientists to develop advanced algorithms and models. Research and validate potential biomarkers associated with breast cancer progression, treatment response, or patient outcomes, using
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! Neuromorphic computing is a way to do computations with hardware that mimics the architecture of the brain. This project aims to explore and benchmark the potential of new neuromorphic hardware and algorithms
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development with Python Experience of machine learning with PyTorch Good knowledge of machine learning and computer vision algorithms Ability to work on own initiative and in a team Experience in collaborative