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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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materials in the steel industry. Using Dynamic MFA with alloy-level tracking, it quantifies flows and stocks of elements such as copper, chromium, nickel, molybdenum, vanadium, and niobium. The research
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critical materials in the steel industry. Using Dynamic MFA with alloy-level tracking, it quantifies flows and stocks of elements such as copper, chromium, nickel, molybdenum, vanadium, and niobium
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data governance, especially in relation to equity and sustainability. Familiarity with socio-legal literature and qualitative research methods. Experience working with social movements and civil society
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passionate atmosphere. The themes of Health and Well-being, Social-Cognitive-Affective Decision Making, Development and Learning, and Advanced Behavioral Research Methods guide research and education. The
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Behavioral Research Methods guide research and education. The institute values conducting these activities in a safe and inclusive environment and provides space for new developments such as open science
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methods. They will be responsible for characterizing the mechanisms of novel bioactive compounds and the medicinal chemistry optimization of these molecules. The candidate will be trained in a variety of
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control over generative shape optimisation. 2 – Explainable AI with LLMs for Transparent Decision-Making in Design Engineering This project combines classic XAI methods with LLM capabilities to generate
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control over generative shape optimisation. 2 – Explainable AI with LLMs for Transparent Decision-Making in Design Engineering This project combines classic XAI methods with LLM capabilities to generate
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networks, or network science, and relevant background knowledge n methods in machine learning and AI. The successful candidate will focus on innovating the field of network analysis with AI methods. Examples