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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health
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expected to teach relevant courses at the bachelor’s and master’s levels with supervision from colleagues. Lastly, you will be advising students at all levels, including Master and PhD students
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patent filings. The work will be centred around topics such as machine learning for communications, communication theory, signal processing for communications, coding theory, and information theory. Your
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comes with no teaching obligations BASIC RESPONSIBILITIES AND OBLIGATIONS Conducting research related to the scientific project titled “Calculus of variations in machine learning problems”, in particular
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for candidates to have the following skills and experience: Essential criteria PhD qualified in mathematical, physical or computational sciences Experience in using machine learning methods to analyse datasets
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topics: Free space optical communication Visible light communication DSP for coherent optical communication Machine learning and AI-native physical layer design Optical reconfigurable intelligent surfaces
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, LHC , Machine Learning , Neutrino , Neutrino physics and Astrophysics , Phenomenology , Quantum Field Theory , Theoretical Particle Physics , theory , Lattice QCD Appl Deadline: 2025/12/01 11:59PM
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reinforcement learning and other approaches for cross-domain generalization Qualifications Essential: PhD in Computer Science, Machine Learning, Computer Vision, Natural Language Processing, or closely related
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Description The Robot Learning & Control Lab (REAL Lab) at NYU Abu Dhabi is seeking an outstanding Post-Doctoral Associate to contribute to cutting-edge research in robot intelligence, machine
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of recruiting talent aligned to these values. We are looking for a Postdoctoral Research Fellow who has: a PhD (or in near completion) in the relevant fields of Artificial Intelligence, Machine Learning, HCI