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imaging, digital pathology, and spatial omics datasets for research projects. - Support computational image analysis, data annotation, and quality assurance activities using established software tools and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 8 hours ago
cytogenetic image analysis. This position is central to a funded research program developing single-cell integration frameworks and AI imaging tools to understand how genome structure and molecular state
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collaborative research in a multidisciplinary environment. Experience with analytical tools such as X-ray diffraction, SEM/TEM, FTIR, and Raman spectroscopy. Ability to communicate effectively and on a timely
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, heating technologies. Experience with analytical tools such as X-ray diffraction, SEM/TEM, FTIR, and Raman spectroscopy. Ability to conduct both independent and collaborative research in a multidisciplinary
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Strong programming expertise in Python and experience with frameworks such as PyTorch, Hugging Face Transformers, or equivalent tools Demonstrated ability to develop scalable, automated, and reproducible
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, Organometallic, Organic Chemistry and Machine Learning for a period of up to 24 months. The project, funded by EPSRC, will involve exploring the use of machine learning to develop new tools for investigating
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in computational fluid dynamics Experience in computer programming, in particular Python and Matlab, and in CAD and CAE tools Ability to work independently and also to enjoy collaborating with others
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University of California, Los Angeles | Los Angeles, California | United States | about 16 hours ago
activities may include analysis of whole-genome and next-generation sequencing data (including quality control, variant calling, annotation, filtering, genetic association, and biological interpretation
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: - Build a ultrafast electron microscope - Combine the tools and techniques of electron microscopy and ultrafast spectroscopy - Plan undergraduate lectures - Write grants - Interact and train graduate
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Learning for a period of up to 24 months. The project, funded by EPSRC, will involve exploring the use of machine learning to develop new tools for investigating catalytic reaction mechanisms, with a focus