23 learning "https:" "https:" "https:" "https:" "https:" "https:" PhD positions in Switzerland
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: https://intranet.basel.institute/job/apply/88 . Applications will be reviewed on a rolling basis. For further information about this position, please contact Dr Claudia Baez Camargo, Director of
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Lebensverläufe nach schwierigen Erlebnissen in Kindheit und Jugend» an. Interessierte Personen bitten wir, sich zur Vorbereitung mit diesem Projekt vertraut zu machen: https://www.nfp76.ch/de/ZYwwIq4IOWL9kQwd
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machine learning. The project focuses on the discovery of governing equations and constitutive relations for key multiphysics phenomena on the basis of rich micromechanical and experimental data. It pushes
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modelling satellite imagery and textual conflict data. Advances in vision-language representation learning will be explored to link the two sources of information through alignment pipelines, localisation
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has more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to
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machine learning approaches for signal classification • Collaborate within an interdisciplinary team of physicists, chemists, molecular life scientists. • Present your findings at conferences and in
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thermochromic molecular switches, and investigate how their interactions can be engineered to produce quantifiable memory and learning behaviors. Your tasks Synthesize libraries of single-, dual-, and
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cellular dynamics are expressive enough to map any source to any target state, but they fall short of learning the underlying regulatory principles. We work on regularization, training on time-resolved
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the basis in thermodynamic mixture properties to conceptual process design for chemical plastics recycling, by linking advanced machine learning techniques with high-throughput experimental methods
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. You are interested in pro-environmental behavior and behavior change. You have excellent knowledge of research methods and statistics and are interested in learning new methodological approaches