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research stays at partner institutions representation of the project at national and international workshops and conferences, as well as contribution to scientific publications Requirements: completed
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data (sequences and associated properties), adapting existing generative architectures (e.g. VAEs and diffusion-based models when appropriate) to the peptide domain, and defining suitable representations
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integration of interdisciplinary competence in education. CINPLA addresses learning and representation in natural and artificial intelligence systems in concert. Artificial intelligence has become a technology
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Engineering Apply for this job See advertisement About the position Position as PhD Research Fellow in formal methods and knowledge representation available at Department of Informatics. The fellowship period
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proficiency – 20%; - Criterion 4: Interest in conducting research and knowledge in the fields of Artificial Intelligence, Data Analysis and Transformation, and Spatio-temporal Data Representation – 40%; VII.III
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Life and Health Sciences Research Institute (ICVS), from the School of Medicine (EM) of the University of Minho | Portugal | 3 days ago
call for applications is now open for the attribution of 1 (one) Research Fellowship for Master Enrolled in a Non-Academic Degree Course, within the scope of the R&D project “Mapping neural representation
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representations of knowledge. via Unsplash Qualifications Required qualifications: Master’s degree in humanities or social sciences, such as cultural or linguistics studies, museology, anthropology, history
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of publications in relevant domains (informatics, machine learning, AI, knowledge representation) Experience with multi-site data harmonization or federated data environments Special Instructions Priority
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representation in natural and artificial intelligence systems in concert. Artificial intelligence has become a technology of great importance to science and education and is interdisciplinary in its nature. INTED
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to develop new knowledge and skills in Artificial Intelligence, Generative Models, and Computational Neuroimaging.. Work plan: 1. Review and analysis of the literature on generative models guided by