3 machine learning positions at Università degli Studi di Trieste

Disentangling heteRogeneity in autism: from EArly behavioral markers to individual treatment responses through a Machine learning approach (DREAM)

machine learning and deep learning approaches, the heterogeneity of autism under the lens of early motor and gestural development, trying to identify: (i) new early behavioural markers of autism risk; (ii

Optimization Strategies for Testing and Improvement of Digital Twins

digital twins. The candidate is expected to have some knowledge of probabilistic machine learning, probabilistic programming, generative models, evolutionary algorithms, and experience with cyber-physical

Calculation of drag reduction in graphene through neural-network molecular dynamics simulations

drag reduction in graphene with a combination of electronic structure methods and large-scale atomistic molecular dynamics (MD) powered by machine learning and high-performance computing (HPC). The first