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the complex multiscale nonlinear interactions at the origin of such extreme events. In this project, you will develop machine learning-based reduced-order models which can accurately forecast
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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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model for transition to a psychotic disorder in children and adolescents using a risk calculator." The project aims to study the population at risk of developing a psychotic disorder by creating a
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group at the University of Cantabria is seeking a PhD researcher with expertise in Life Cycle Assessment (LCA) to contribute to ongoing research projects focused on sustainability assessment and
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. Requirements: PhD completed less than 7 years ago in Computer Science or related areas; experience in machine learning and data science (supervised/unsupervised models, recommendation and evaluation/robustness
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of advanced ab-initio computational methods for modeling electronic and magnetic properties of low-dimensional systems; - documented organizational activities (supervision of students and PhD candidates
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to the provisions of the regulations governing calls for applications of research staff to cover contractual positions assigned to research projects, available at the following website address: https://s.ua.es/es
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Application deadline: 30/04/2026 Research theme: Nuclear Engineering How to apply: https://uom.link/pgr-apply-2425 This 3.5-year PhD project is fully funded; home students are eligible to apply
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, the postdoctoral researcher will be responsible for contributing to the development of advanced methodologies for predicting crystal structures (CSP) based solely on their chemical composition and atomistic modeling
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 2 months ago
Europe Research and Innovation Programme under the Grant Agreement No.101178775 Workplan: Design, develop and implement deep learning methodologies for generation of subsurface earth models. Duration