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Development of innovative experimental model systems for mechanistic investigation and translational validation of microbiome-mediated processes Advanced AI and machine learning frameworks for integrative multi
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predictive machine-learning models from heterogeneous data. DSIP is actively collaborating with industrial partners and research organizations. DSIP is involved in developing Deep Learning solutions for time
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of Business Intelligence (machine learning & LLM) to enhance the sustainability of regional tourism. On the supply side, a monitoring system is developed by extracting data from online platforms such as Google
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using machine learning methodologies; (2) the extension of an existing CFD framework for multiphase modeling to the case of PEC systems; (3) the implementation within the framework of a description of
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: Dep.of Ingegneria Duration: 12 months Where to apply Website http://www.unife.it Requirements Additional Information Eligibility criteria Eligible destination country/ies for fellows: Italy Eligibility
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Offer Description Development of atomistic ab-initio simulations and machine learning models for the study of phonon transport, phase transitions, and structural optimization of phase change materials
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Engineering, Computer Science, Telecommunications, or related areas. Solid background in signal processing, wireless systems, applied mathematics, and/or machine learning. Proficiency in programming (e.g
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; Distributed multi-agent sensing and cooperative positioning algorithms; Machine learning and data-driven methods for ambient awareness. Working Environment: The PhD will be conducted at the University
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Science, Telecommunications, Applied Mathematics, or related fields; Solid background in probabilistic modeling, Bayesian inference, information theory, and/or machine learning; Experience with signal processing or decision
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, stochastic differential equations, computational methods in fluid mechanics and turbulent flows, high-performance computing, machine learning methods in computational problems. GSSI is a world-renowned