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computational mechanics and scientific machine learning. The successful candidate will work on the design of hybrid, physics-informed modeling and identification frameworks for complex dissipative material
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24 Jan 2026 Job Information Organisation/Company Università degli Studi di Padova Research Field Engineering » Computer engineering Researcher Profile Recognised Researcher (R2) Leading Researcher
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) training personalized computational models in new contexts, and (iii) studying in-silico clinical intervention strategies. The postdoctoral fellow will have the opportunity to: Learn about computational
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complex behavior under demanding operating conditions presents a significant modeling challenge. This project addresses that challenge by combining machine learning with constitutive modeling, while
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) training personalized computational models in new contexts, and (iii) studying in-silico clinical intervention strategies. The postdoctoral fellow will have the opportunity to: Learn about computational
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modelling predictions. Experience or a strong interest in scientific programming and machine-learning-assisted data analysis for materials modelling is an advantage. PhD Position 2 – Coarse-Grained and
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experience in scientific programming is a plus. • Experience in constructing Machine Learning potentials would be appreciated. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR5254
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a skilled Data Scientist with a strong foundation in genomic biostatistics to join our team. This role involves leveraging advanced statistical methods and machine learning techniques to analyze
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of linguistic corpora, the development and use of Machine Learning and Artificial Intelligence models for the prediction, categorization, and automatic evaluation of pragmatic aspects of language, up
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at finale.seas.harvard.edu and our group’s webpage https://dtak.github.io/ We work on probabilistic models, reinforcement learning, and interpretability + human factors. Basic Qualifications Candidates are required to have