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Field
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in computational methods, particularly those with backgrounds in machine learning, artificial intelligence (AI), statistics, bioinformatics, or analysis-acceleration technologies. Candidates should
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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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Monitoring Drift Chambers (MDT), and in the Event Filter track trigger (EFTracking). The group applies novel Machine Learning tools and techniques to both analyses and trigger upgrades, and leverages FPGA and
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virtual reality development, machine learning, or advanced data analyses and modeling are highly desirable. Position Status Full Time Posting Number 25FA0682 Posting Open Date Posting Close Date
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-relationships, materials optimization, materials under extreme conditions, and generative AI. Candidates must possess substantial experience in artificial intelligence and machine learning methods, specifically
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geometries. However, AM-generated surfaces exhibit significant and highly irregular roughness, a key factor that strongly modifies turbulence, pressure drop, and heat transfer. Unlike conventional machined
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 25 days ago
hyperscanning neuroimaging data, using advanced statistics and machine learning methodologies for temporally-sensitive data, such as GLMM, Random Forests, LSTM, etc.. Use of MatLab for pre-processing, and
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of sea turtles - Developing innovative machine learning methods to analyze the sounds associated with these behaviors - Automating the processing of audio and visual data to optimize the quantity and
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, development of chemical process solutions for repurposing of electrodes, and integration of AI-based vision and active machine learning to optimize the efficiency of the process. Writing publications and
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subsea digital twin of deep-water mooring lines for floating offshore wind turbines. The digital twin will be integrated with machine learning algorithms for detection of primary entanglement due