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/ machine learning algorithms to support research in the IDMxS Analytics Cluster. The RF will apply/ improve machine learning algorithms to process (e.g., classify, predict) data collected by IDMxS. Help
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. Job Requirements: PhD degree in Computer Science, Computer & Electronics Engineering or other related fields. Strong background and knowledge in at least one or preferably more of the following fields
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Responsibilities: To perform pioneer research in scent digitalization and computation. To further develop machine learning tasks for scent signal classification/fusion. Set up and analyze experiments under different
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, electrical & electronic engineering, or equivalent. Background knowledge in signal representation/processing, visual data compression, and data-driven and machine learning/analysis. Prior research experience
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into products and services for Continental through close collaboration with its business units. Key Responsibilities: To independently undertake research in artificial intelligence, machine learning system, edge
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testing data Development of machine learning models for battery health assessment and remaining useful life prediction Job Requirements: PhD degree in Electrical Engineering or related subjects. Expert
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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requirements: PhD degree in Computer Science, Electrical and Electronic Engineering, or related field. At least 3 years of relevant experience in computer vision, artificial intelligence, etc. Proficiency in
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areas. Key Responsibilities: To independently undertake research in computer vision and machine learning. To produce research reports and/or publications as required by the funding body