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Field
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established methods of microstructural analysis and mechanical testing with new schemes such as Acoustic Emission for non-destructive assessment of degradation and Machine Learning for development of predictive
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the trusting; and the situations where we are more likely to ‘outsource’ moral decisions to AI agents. By understanding this, we consider the ethical promise and pitfalls of such moral machines and how
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, working closely with data scientists, oncologists, and international collaborators. The research will inform real-world decisions in oncology and contribute to tools that improve patient care. We’re looking
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of the Discrete Choice Experiments in Mozambique and South Africa, and the analysis of the ensuing data Develop computational models of health actors’ decisions and responses to regulatory options Collaborate with
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relationships. You are motivated to acquire new skills and work in a multidisciplinary team. You have practical experience with experimental work and data analysis. You act with attention to quality, integrity
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that respond to climate change impacts on agriculture and aquaculture. Using the DROPapp, you will support decisions on crop calendars, salt-tolerant varieties, water management, and early warning-based actions
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Decision Intelligence for Supply Chain and Operations Optimization. The successful candidate will contribute to cutting-edge research at the intersection of Statistical Machine Learning and Generative
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for health policy decision-making, these methods will be developed using a Bayesian framework. This PhD project will deliver a substantial contribution to original research in the area of health data science
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subprojects (SP): 1) SP1 includes desk research and case file analysis about how decisions are based on what kind of legitimations 2) SP2 unfolds how decisions are justified in-the-making via shadowing and
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research and case file analysis about how decisions are based on what kind of legitimations 2) SP2 unfolds how decisions are justified in-the-making via shadowing and narrative interviews 3) SP3 focusses