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Field
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years, practitioners and researchers have realized that predictions made by machine learning models should be transparent and intelligible. Although explainable AI methods can shed some light on the inner
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work, conducting an interview about the style and technique, or analyzing how museum professionals present objects to the public, emphasizing and re-articulating some aspects of their provenance and the
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professional network among researchers, artists, and museum specialists. A typical day may include filming a ceramist at work, conducting an interview about the style and technique, or analyzing how museum
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novel materials, tools, or artistic creations, humans instinctively explore the unknown in order to acquire information about it, to make sense of it, to act on it, and to appreciate what is in front of
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foundational theory and real-world impact. Consortium This position is part of a European Doctoral Network consortium REUNATECH- NATECH Risk Management and Resilience of High-Tech Industries and Critical
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to staff position within a Research Infrastructure? No Offer Description Our theory group is a worldwide leader in studying the statistical physics of living systems, ranging from chromosomes
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to staff position within a Research Infrastructure? No Offer Description Our theory group is a worldwide leader in studying the statistical physics of living systems, ranging from chromosomes
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Join us to explore the mechanics of soft matter through a unique blend of theory, hands-on experiments, and machine learning. Job description Soft matter such as polymers and hydrogels
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subgroups—in shaping how teams collaborate and perform under pressure. By advancing knowledge on these dynamics, we seek to contribute to both scientific theory and practical solutions for organizations. Your
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environment that brings together expertise in computational design, digital fabrication, and architectural history/theory. The project will be situated within ongoing explorations of robotic fabrication