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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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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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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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like computational complexity of algorithms. It’s also fairly common that we need to drill down into the code for some tool to figure out what’s wrong, so being able to read and understand code is
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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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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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-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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You will be working in a larger research and development project in parallel, distributed and heterogeneous computing. The project work can, under certain circumstances, be combined with an internal
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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