10 machine-learning "University of Zurich" scholarships at Vrije Universiteit Amsterdam (VU)
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robot learning & representation learning. You will be jointly supervised by the Assistant Professors Kevin Sebastian Luck (Computational Intelligence Group) and Shujian Yu (Quantitative Data Analysis
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solely on machine learning (ML) is neuro-symbolic AI, i.e., synergistically combining the neural AI tradition via deep learning and artificial neural networks and the symbolic AI tradition via knowledge
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) and phenotypic data with artificial intelligence and machine learning techniques. Phenotypic data will include data from available strain collections with sequenced strains and information
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computer systems, including topics such as compilers, operating systems, computer architecture, and computer networks you have demonstrable strong knowledge and skills in systems security, including topics
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or similar field. You have an interest in human-computer interaction, intelligent user interfaces, hybrid human-AI intelligence or similar topics relevant to the position. Interest in knowledge graphs, digital
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be developed to differentiate kindergartners based on their potential for learning to read rather than their current knowledge, with the aim to make it less biased. In this PhD project, you will obtain
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hydrological science with decision and behavioral theories from social sciences. As parts of these topics may be new to you, you are open to learn in an interdisciplinary environment together with researchers
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(or willingness to learn) preferred. Master's degree in a field related to dentistry, biomedical sciences, biomedical technology, bioinformatics, health sciences, or correlated field. Expertise in and affinity with
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car insurance); Additional comments Are you interested in this position and do you believe that your experience will contribute to the further development of our university? In that case, we encourage
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European perspective. The project will be supervised by prof. Hemme Battjes and dr. Martijn Stronks. Your duties learn to independently conduct high-quality research, culminating in PhD thesis; collaborate