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Field
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requirements: Experience using deep-learning algorithms. In-depth knowledge of Python and PyTorch. Previous experience collaborating on scientific projects. Publications on deep-learning topics. 4. Work Plan
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be duly proven at the time of hiring. 2; 3. Preferred requirements: Experience using Machine Learning algorithms. In-depth knowledge of Python and PyTorch. Previous experience collaborating
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a PhD student, you will develop state-of-the-art learning and inference methods to detect and characterize anomalous radio behavior and to design algorithms that remain reliable under practical
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for, and mitigating weather and hydrological extremes, as well as to develop effective decarbonization strategies. The possible role of AI ranges from predictive models of solar insolation and wind variables
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simulations on the Aurora supercomputer, using AMReX (https://amrex-codes.github.io/amrex/ ) and the lattice Boltzmann method (LBM). The candidate will develop flow/geometry-aware refinement strategies that go
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) develop a methodology based on image processing algorithms to correct movements not caused by mechanical excitation of the retina; iii) evaluate the feasibility of passive retinal OCE with excitation based
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for Smart Cities of Tallinn University of Technology (TalTech) invite applicants for a 4-year PhD position in the field of responsible AI governance for smart city development. The project focuses on how
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University, to begin as early as July 1, 2025. Topics include the experimental quantum simulation of chemical and condensed-matter systems using 1D and 2D ion arrays, and the development and optimization
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will be involved in the Trusted Autonomous and Self-Adaptive Systems for Defence (SAACD) project. This project aims to overhaul the engineering and development of this type of complex system. A SAACD can
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of Geodesy and Earth Observation (GEO). In this position, you will develop algorithms and methods aimed at improving GNSS position integrity and mitigate/reduce both natural and intentional signal interference