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of scientific data, e.g. from image acquisition modalities or scientific simulations. Efficient algorithms are at the core of most of these data analysis and visualization applications. The focus of this Ph.D
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with machine learning and generative AI algorithms, with working knowledge of deep learning frameworks such as PyTorch or TensorFlow is considered a strong advantage. • Extensive experience in multi
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postdocs (2 years each) research/consumables funding Work assignments As an Assistant Professor, you are expected to conduct and lead pioneering research that combines fundamental and applied aspects of soft
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CST Microwave Studio, HFSS or EM Pro for antenna modeling and design is required, as is experience with programming languages like MATLAB, Python, or similar for antenna array analysis and algorithm
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and development of algorithms, methods, and theories aimed at better understanding the properties and underlying mechanisms within statistical and deep learning-based systems also in the presence
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distributed across social space, whether residential, organizational, or relational. Segregation is a recurring topic in analytical sociology, offering a key example of how interacting individuals may
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, postdocs, researchers, and industry. Your qualifications You have graduated at Master’s level or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses in
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-taking mechanisms, and/or experience of running distributed organizations. Ability to build communities and engender a common sense of purpose within them. Awareness of data science and AI challenges
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of the functioning of the European Commission and understanding of its funding and decision-taking mechanisms, and/or experience of running distributed organizations. Experience of the delivery of large and complex
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, the random dropout of participating agents, and uneven distribution of data across agents. As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part