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optimization of multi-modal LLMs. Investigate and implement methodologies to ensure AI authenticity, accountability, and the integrity of digital content. Develop and refine machine learning and deep learning
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thermodynamics Design and implement machine learning models for data collection, reduction, analysis, and visualization. Work creatively, independently, and productively. Work as a member of a multidisciplinary
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | 3 months ago
both the NCRC in Kannapolis and UNC Charlotte in Charlotte. Experience in yeast genomics, RNA-sequencing, bioinformatics, or machine learning is preferred. Departmental Preferred Experience, Skills
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approaches that address (for example) the intellectual status of the image, the political functions of art, or visual theology across multiple regions. The Mellon Fellow will teach two courses per year: one
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testing of machine learning/AI algorithms Integration of radiomic and biological datasets Working closely with Medical Physics colleagues on reviewing recommendations for detection of specific metabolites
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characterization. Experience or interest in conducting interdisciplinary research, particularly in the intersection of machine learning and materials informatics. Ability to work effectively in an interdisciplinary
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postdoctoral fellow interested in learning and using contemporary functional genomics approaches (CRISPR, RNAi, transgenics, etc.) to characterize the functions of genes involved in biological development
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models using frameworks such as PyTorch and TensorFlow. Research experience in medical image analysis using deep learning algorithms. Strong track record in machine learning, computer vision, and medical
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as world-leading or internationally excellent. We use this expertise to teach the next generation of health professionals and research scientists. Based across King’s Denmark Hill, Guy’s, St Thomas
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available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research on Riemannian Optimization. The ideal candidate has a