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of the ERC Consolidator project AUTOMATIX (see details below), we are seeking a PhD candidate to develop machine learning approaches for constitutive modeling. Context With the advent of machine-learning (ML
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mechanics, finite element modeling, and scientific machine learning. The RSE will contribute to the design, implementation, and maintenance of open-source software libraries that integrate phenomenological
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for part-time employment. Starting date: 14.01.2026 Job description:PhD position on physics-based machine learning modeling for materials and process design Reference code: 2026/WD 1 Commencement date
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researcher will work at the interface of root developmental biology, 3D modeling, network and graph theory, and data analysis, in close interaction with biologists, modelers, and computer scientists (INRAE
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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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interest in the total affairs of the college. Under general supervision, this individual will prepare and teach computer integrated machining courses designed for career technical programs. The faculty
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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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project involves interdisciplinary research at the interface of computer science and mathematics, with a focus on bivariate molecular machine learning for modeling molecular interactions and properties
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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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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