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Dipartimento di Ingegneria dell'Informazione - Università degli Studi di Padova | Italy | about 1 month ago
immersive and interactive environments. • Definition and modeling of low- and high-level quality-related features. • Development and validation of objective quality assessment metrics for synthesized content
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during surgery or endoscopic exploration. This postdoctoral position aims at developing innovative deep learning algorithms to help histology classification. Both classical histology based on hematoxylin
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within a Research Infrastructure? No Offer Description Group Leader in Quantum Algorithms and Machine Learning (f/m/x) Ref. Number: MAB/06/2026 Location: Warsaw, Poland Salary: 20 750 - 24 250 PLN/month
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) to join a dynamic, interdisciplinary research team. Our team performs health economics research to better understand and develop policies to lower health care spending and improve healthcare delivery and
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of reinforcement learning and popular modern reinforcement learning algorithms. Students will develop familiarity with both model-based and model-free reinforcement learning algorithms, including Q-learning, Actor
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(LES) results. Key Responsibilities: Develop and refine numerical algorithms for real-time wind field forecasting. Validate forecasting models against high-fidelity LES data and field measurements
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, quantitative analysis, performing medium-scale microscopy experiments, Python or Matlab programming, synthesizing information from the published literature, and use and development of machine learning algorithms
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to insert (known as injection) modified or forged media (images or videos) into communication channels to defeat matching algorithms, presentation attack detection, or human reviewers. Protections against
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of the center's researchers. Integrate precipitation data to support the maintenance and improvement of algorithms for improving precipitation estimates by combining radar and rain gauge data. Develop methods
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. Integrate precipitation data with collaboration in the maintenance and improvement of algorithms for improving precipitation estimates by combining radar and rain gauge data. Develop methods