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that support more integrated preventative approaches to complex needs. This interdisciplinary project is ideal for students interested in applied data science, public policy, and improving outcomes
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AI training has emerged as the standard approach, which utilizes thousands of high-performance devices within a data center to collaboratively process tasks. When they are even more complex, the
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combine multiple techniques, picking those that complement each other. In particular the use of non-destructive techniques is important, avoiding unintentional sample modifications. Although such “hybrid
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the need for sustainability to achieve Net-Zero goals. Cyber-Physical Systems (CPS) integrate machines, robots, and AGVs, but challenges like mechanical wear and electronic errors pose risks to efficiency
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characteristics might explain these differences? MS is a complex disease, with damage to the brain and nervous system that varies widely between individuals. This PhD project offers an opportunity to investigate
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three interconnected groups: Occupational Health, Planetary Health, and the Data Science & Exposome Group. Our mission is to advance education and cutting-edge research to unravel the complex interactions
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Health, Planetary Health, and the Data Science & Exposome Group. Our mission is to advance education and cutting-edge research to unravel the complex interactions between environmental factors — including
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will be guided to create interactive outreach throughout your research process in the form of visual media, installations, social media posts and other outlets. It is expected that PhD candidates spend
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glycosylation, the most complex cellular enzymatic process chemical or chemoenzymatic synthesis of glycan-based reporter molecules and small molecule inhibitors contribution to scientific primary publications
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issues like climate change, biodiversity loss, and environmental degradation. We aim to understand the interactions within social-physical systems, considering land uses and diverse stakeholders. The chair