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Field
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learning-assisted computational pipeline for the automated detection of point defects in atomic-resolution scanning transmission electron microscopy (STEM) images. Using monolayer MoS₂ as a model system, the
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will entail movement among the open office space, the galleries, and the campus and community, along with use of computer and audio/visual equipment and the lifting of materials of approximately 35
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Radiology faculty collaborator, to define and address clinically meaningful research problems. • Design, implement, and evaluate machine learning and AI methods for medical imaging using real-world clinical
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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looking for postdoctoral researchers in the area of computer vision, AI, and machine learning. The initial appointment will be for 2 years with a possible extension with a tentative start date in January
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the Lotfollahi Lab – leaders in generative AI and foundation models for spatial and single-cell genomics – you will develop and apply state-of-the-art machine learning approaches to large-scale spatial genomics
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techniques. You will have the opportunity to participate in various projects utilizing artificial intelligence (AI) and machine learning (ML) to develop applications that optimize combat casualty care
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to multidisciplinary research aimed at advancing military medicine. What will I be doing? This opportunity offers a hands-on learning experience within a collaborative research environment focused on combat casualty
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an outcome focused and inclusive workplace. To learn more about our culture and hiring process, visit our Jobs at Macquarie page.
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hours in the space allocated to the group in London (fully remote work is not possible). The postholder can expect: Provision of a quiet work space, a computer, access to high-performance computing, a lab