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of the Ministry of Higher Education and Research (MESR). The project focuses on the development of cutting-edge machine learning methods aimed at predicting atomistic structures (i.e., the arrangement of atoms
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(which is often easier to create particularly in for multilingual processing typically by using machine translation) and further improving the model using preference data. Preference learning has gained
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selection, the marginal likelihood, and generalization. In International Conference on Machine Learning, pages 14223–14247. PMLR, 2022. [8] B. O. Muth ́en. Beyond SEM: General latent variable modeling
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. The PhD candidate will be in charge of i) the development of cutting-edge machine learning models correlating materials synthesis protocols with materials properties, and of ii) using such models in
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the suited security micro-services. This automation is made possible by formalizing micro-services-based applications and their data-flows, and machine learning techniques for selecting the micro-services
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learning new techniques and finding answers to problems. You want to take advantage of the opportunity to do your PhD in two different countries and learn from different cultures and expertise. Where
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climatic conditions, using machine learning approaches based on isotopic data. SSIAs for δ13C, δ15N and δ34S in dentin collagen and δ66Zn in enamel to reconstruct the evolution of seasonal habitats and the
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strong interest in computer science (software development, machine learning techniques, etc.) is desirable. · Applicants must have a maximum of 3 years of research experience after the PhD. · Language
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will focus on studying the principles of neural computation through recurrent neural networks, dynamical systems theory, and machine learning. - Develop mathematical and computational models of neural
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the field of algorithm configuration and selection in a streaming fashion by investigating techniques that continuously optimize machine learning models as new data instances arrive [2]. A key focus will be