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to humans and are accessible to algorithmic techniques while neural models are adaptive and learnable. The aim of this project is to develop models which combine these advantages. The project includes both
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interdisciplinary research on knowledge extraction from social data. Project description The project is in the emerging area of fair social network analysis. In today’s algorithmically-infused society, data about our
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EMBL Partnership for Molecular Medicine, which is dedicated to the growing field of life sciences that investigates the molecular basis of disease and explores molecularly and genetically based
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molecularly and genetically based treatments. Eligibility requirements Applicants meet the basic eligibility requirements for doctoral studies if they have: Completed a second-cycle (Master’s level) degree
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, algorithms, and programming. Knowledge and experience in artificial intelligence and machine learning is expected, but not required. Knowledge and experience in deep learning and generative AI is considered
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cellular mechanisms to the biology and welfare of various animals. Our activities cover a broad spectrum of disciplines, including anatomy, physiology, genetics, breeding, biochemistry, pathology
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anatomy, physiology, genetics, breeding, biochemistry, pathology, pharmacology, toxicology, immunology, microbiology, bioinformatics, and One Health. We study production animals, companion animals
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microbial ecology, biotechnology or microbiology. very good oral and written proficiency in English. excellent laboratory skills in microbiology. knowledge and related skills pertaining to genetically
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and algorithmic foundations for goal-oriented, semantics-aware communication strategies that enable efficient, intelligent, and adaptive information exchange in joint communication and control. In
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the European Regional Development Fund. Subject description The subject includes signal processing with emphasis on development and optimization of algorithms for processing single and multi-dimensional signals