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Field
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professionals to accelerate scientific discovery and engineering advances across a broad range of disciplines. As an important part of the broader High-Performance Computing (HPC) infrastructure, the division
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symbiosis. This project aims to bridge financial modelling, AI, simulation, and circular business model innovation, equipping decision-makers with practical, scientifically grounded tools to evaluate risks
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prognostic markers for psychosis in youth at clinical high risk, using state-of-the-art AI models and multimodal neuroimaging, clinical, and cognitive data. The position will emphasize advanced computational
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of Dermatology, University of Pittsburgh School of Medicine Advance skin-targeted biomedical technologies at the engineering-dermatology interface! The University of Pittsburgh School of Medicine’s Department
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mechanisms of cardiac arrhythmias. Our research integrates genetically engineered mouse models, cardiac electrophysiology, ion channel biology, and translational cardiovascular research to investigate how
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and implement AI(ML/DL)-based predictive frameworks to assess water availability, drought impacts, groundwater depletion, and salinity risk under climatic and anthropogenic changes. Lead data collection
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from striving for excellence within specialized disciplines, it is our vision to foster interdisciplinary collaboration between health professionals and engineers, focusing on finding solutions
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Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig | Leipzig, Sachsen | Germany | 3 months ago
) Requirements PhD in physics, biomedical engineering, neuroscience, or related field Strong experience in MRI acquisition and neuroimaging methods Solid programming skills (Python, MATLAB, or similar) Experience
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Department of Economics conducts research and teaches in both business administration and economics. Unique to the department is that great importance is placed on applied science, often in collaboration with
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alerts that flag injury risk during the training season. Vet Vision AI has developed this technology to characterise behaviour in healthy horses and to detect patterns associated with disease in