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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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Cacciotti, Full Professor and Coordinator of the Ph.D. Course in Advanced Modelling, Materials and Technologies (AMOMAT). The Research Group has consolidated experience in the formulation, synthesis
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or runtime verification techniques for continuous dynamics and hybrid systems; Development of formal verification techniques and their integration in model-based design environments; Model checking of embedded
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processes, multimodal data fusion, physics–ML hybrid modelling (from CFD to atomistic simulations), and AI-assisted hypothesis formulation. MSCA Doctoral Candidate eligibility criteria Applicants must comply