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Field
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methodology will involve the development of mathematical models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation
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. This involves the development of mathematical models for signal transmission/reception, derivation of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or
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• Develop, consolidate, and optimize fMRI and EEG neurofeedback algorithms. • Design, integrate, and test standalone neurofeedback software (software suites for clinical environments). • Contribute
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, chemical fixation and resin embedding, FIB milling, cryo preparation) Experience in developing and using correlative workflows, data processing and data visualisation, including methodologies and algorithms
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for the design and the benchmarking of algorithms tailored for photonic quantum computation. The outcome of the project will be the assembling of three prototypes: ● QSPACE, machine encoded in spatial modes and
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want to understand the fundamental principles that permit us to build privacy-aware AI systems, and develop algorithms for this purpose. The group collaborates with several national and international
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Interatomic Potentials) code for ternary compounds with variable composition with crystal structure optimization algorithms (evolutionary, random, etc.); - Application of the CSP DFT/MLIP methodology to various
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researcher in algorithmic game theory and/or online learning, working with Prof. Celli at BIDSA and the Department of Computing Sciences. The project studies how multiple machine learning algorithms interact
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to process the quantity of experiments conducted with one or more fish swimming simultaneously, on the one hand; and on the other hand, to implement a data fusion algorithm to improve the overall precision
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, or the design of efficient, explainable, and scalable query engines. The successful applicant will help design and build novel systems and algorithms that challenge traditional assumptions in databases, guided by