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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 2 months ago
scalable computational algorithms and translate the proposed methodology into practical applications. We are seeking applications from candidates with either a track record or proven potential in research in
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Publications: 1. P. Chen et al., Ultrafast photonic micro-systems to manipulate hard X-rays at 300 picoseconds, Nat Commun, 10:1158 (2019). https://doi.org/10.1038/s41467-019-09077-1. 2. P. Chen et al., Optics
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languages. The section is part of the Department of Mathematics and Computer Science, and other research sections at the department are Algorithms Computational Science Data Science and Statistics Geometry
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/or R. Develop, maintain, and implement custom scripts for data acquisition, processing, and analysis as well as machine learning algorithms and techniques to classify and predict outcomes based
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Responsibilities Conduct research in computational methods for environmental and engineering applications. Develop and analyze numerical algorithms, reduced-order models, and machine-learning-enhanced simulation
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The position will be attached to the project “SURE-AI” (http://www.sure-ai.no/ ) funded by The Research Council of Norway, and lead by Simula Research Laboratory. The main focus of the research will be
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algorithms to enable autonomous execution of surgical interventions. The research program will include a systematic investigation comparing this autonomous surgical paradigm against expert surgeons performing
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. Responsibilities: Design, develop, and implement state-of-the-art foundation health models and clinical reasoning algorithms. Collaborate closely with top-tier partner universities and clinical/industrial partners
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algorithms. Alliance Liaison Act as CUT’s liaison for WP9 (Communication & Dissemination), coordinating an editorial calendar and collecting content inputs from partner communication teams. Contribute to WP9
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systems in firmware algorithm development and simulation. We are also active in R&D using AI in custom electronics as well as in distributed computing. The Pitt ATLAS Group is led by Professors Joe Boudreau