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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
skills, and interdisciplinary perspectives required to tackle current and future environmental and resource challenges. We encourage engaged service that translates knowledge for the public good. Position
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monitoring. Design and implement machine learning models to analyze multimodal data (e.g., student behavior, engagement, and performance) to enhance personalized learning. Develop and evaluate GPT-powered AI
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effects on acute lung injury after trauma. We use traditional immunology techniques including flow cytometry combined with molecular biology and cloning technologies. Candidates having experience with small
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architectures and patterns for space and ground-segment systems. 2) Digital system security engineering Utilising novel model-based frameworks to facilitate the application of emerging system security standards
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hydrogen storage has definitely been on the rise. Despite these advantages, the current tanks have several issues regarding the liner, such as cavitation and blistering, and others related to the tank walls
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that govern time-dependent spectral energy distributions of black hole accretion disks, applying these models to X-ray and multi-wavelength data to extract empirical constraints on accretion flow physics, and
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policy of the Agency. You are strongly encouraged to familiarise yourself with the technological activities performed by STS PNRR, in particular in the field of Model-based Digital Twin applied
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of liver micrometastases development in cancer, based on a novel MRI approach which combines multi-dimensional diffusion-relaxometry acquisitions, efficient data denoising and biophysical modelling
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reconstitution are poised to transform the field, providing unprecedented insights into adrenal development, disease modeling, and therapeutic innovation. This platform represents a critical step toward
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graduate student Qualifications · Ph.D. in immunology, microbiology, cell biology or related areas · Experience with in vivo animal models or multi-color flow cytometry are preferred · At least one first