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-learning–based segmentation, species classification and lineage tracking workflows for multi-species time-lapse data Optimise models and pipelines for real-time performance, enabling adaptive imaging and
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 1 day ago
– Machine Learning for Quantum Simulation and Computing and Thermal Energy and Process Engineering are looking for a PhD Student (f/m/d) in Quantum Algorithms for Droplet and Bubble Oscillation Dynamics
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education and economic development needs. Federally designated as a senior military college, one of the university's signature leadership programs is its 800-member Corps of Cadets on UNG's Dahlonega Campus
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 15 days ago
: The scholarship holder will acquire electrophysiological data (EEG; ECG; EMG) from healthy and/or stroke patients, involving brain-computer interfacing with VR training in a lab and in a clinical environment
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technological change driven simultaneously by digitization, the application of artificial intelligence and machine learning to all facets of company, economic, and human data, and a new emphasis on the importance
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of Nursing: teach, participate in service-related activities that support the school, and engage in clinical scholarship or practice. As a certified nurse midwife, the faculty member is encouraged to maintain
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Loyd for the application at landon.loyd@aims.edu. Ability to teach using methodologies that support a student-centered learning environment. Computer literacy and the ability to use computer technology
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the complex multiscale nonlinear interactions at the origin of such extreme events. In this project, you will develop machine learning-based reduced-order models which can accurately forecast
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similar to Aims students. Ability to teach using methodologies that support a student-centered learning environment. Computer literacy and the ability to use computer technology in classroom/lab instruction
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minimizing computational and energy costs. The proposed approaches will rely on machine learning methods applied to image analysis, with the objective of enabling early identification of at risk areas and