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for Paediatric Echocardiography Supervisor Names: Dr Patrick McAllister This PhD project will develop and evaluate explainable, domain-adaptive deep learning approaches for image- and video-based classification
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Department of War security clearance. Knowledge, Skills, and Abilities: Deep Technical Knowledge: You have performed extensive research or engineering activities in applied machine learning and artificial
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(PyTorch, scientific Python) with solid experience in scientific computing and software development; familiarity with C++ and Linux environments is an advantage Strong background in deep learning for image
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biophysics and deep reinforcement learning, and Médéric Argentina (INPHYNI, Université Côte d’Azur), an expert in nonlinear physics and learning in dynamical systems. By bridging artificial intelligence and
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-level transformations. Courses are developed specifically for online, asynchronous learning and are designed to meet the needs of working professionals across a range of education-related settings. We
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intelligence throughout the scientific process. During the initial phase of the project, the researcher will spend significant time on-site at Stanford University working with the Schnitzer Lab to learn and
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in Timber Engineering. The Chair educates the next generation of structural engineers, equipping them with deep technical knowledge and top-level competencies in the use of timber as a high-quality
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, Linguistics, Computer Science, Philosophy, Psychology or Neuroscience. Must demonstrate ability to teach effectively in a dynamic learning environment. Must demonstrate experience with, and deep knowledge
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combination of training or experience; or MS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with eight (8) years of experience; or PhD in data science
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alongside boxing clubs as influential community institutions with deep local reach. This PhD will examine the role of Belfast boxing and combat gyms from the 1960s to the present. It will explore how gyms