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Field
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imaging technologies, such as cryo-electron tomography (cryo-ET) and expansion microscopy, have been pivotal in advancing our understanding of the structure and function of motile cilia. In contrast
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principles that regulate host-pathogen interactions and feedback, using a combination of quantitative imaging, microfluidics, statistical analysis and machine learning tools. A specific focus will be put
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laboratory (wind-wave facility) experiments, using state-of-the-art imaging techniques developing computational codes to process and understand large experimental datasets (e. g., image processing) analyzing
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lengthy processing times associated with sequencing. This PhD project aims to develop innovative artificial intelligence (AI) methodologies by integrating histopathology images and RNA sequencing data
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 17 hours ago
related to the cannabinoid and neuroHIV fields, including behavioral pharmacology studies, in vivo calcium imaging studies, as well as studies that focus on harvesting of CNS tissue, and
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scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available to UK (Home) candidates only. Fully-supervised AI techniques have shown remarkable success in
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novel strategies to treat seizures and cytotoxic edema, especially in neonates. To reach this goal, we are addressing the following questions: 1. How does the brain inhibitory system work at the cellular
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Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available
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learning, or signal processing; familiarity with microscopy data is an asset but not required Interest in foundational machine learning research with applied impact in scientific imaging Demonstrated
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well as computational analysis to uncover biophysical principles that regulate host-pathogen interactions and feedback, using a combination of quantitative imaging, microfluidics, statistical analysis and machine