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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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Computational Chemistry, Materials Science, or a related field. Strong background in computational chemistry techniques, including molecular dynamics, quantum mechanical simulations, and machine learning
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solid experience in programming, particularly in Python and JavaScript. Significant experience in data science and machine learning will be highly valued. You like to work in a team while demonstrating
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engineering, or related disciplines who are passionate about applying machine learning to real-world clinical challenges. The successful candidate will lead the development and validation of predictive models
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obtainable using the Oxford Nanopore sequencing platform and improve genome recovery from metagenomes by developing new binning algorithms based on machine learning. Furthermore, the postdoc will aid in
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qualifications: PhD or equivalent achievement (proof of independent research capability) in Machine Learning, Computer Science, Physics, Mathematics, or a related field Deep theoretical knowledge and extensive
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Description The Clinical Artificial Intelligence Lab at NYU Abu Dhabi seeks to improve patient care by developing new machine learning methodologies that tackle unique computational problems in
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vehicle validation. Design and implement machine learning models that capture the complexity and variability of real-world traffic situations, including unusual pedestrian behaviors, edge cases, and multi
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of their research projects, fellows in the Smith lab have the opportunity to work one on one with the PhD biostatistician associated with our laboratory to learn introductory machine learning methodology such as
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execution. This work involves creating frameworks for adaptive decision-making, using techniques from operations research and machine learning. This particular thematic area will be supervised by Associate