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Finn-Eirik Johansen (Department of Biosciences, Faculty of Mathematics and Natural Sciences) and Shuo-Wang Qiao (Institute of Clinical Medicine, Faculty of Medicine). The group’s main research focus is
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cavitation detection, passive acoustic mapping and ultrasound localization microscopy; the development and refinement of relevant pre-clinical models to enhance and validate the safety and efficacy
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community. You may develop projects in fields including • Data and computational science: Bioinformatics, AI/ML, computational modelling, software engineering, data management, data science. • Imaging and
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compliance-by-design AI architectures and models and validate our solutions across key energy use cases such as energy market optimization (demand response, transactive energy peer-to-peer trading, and
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have expertise in one or more of the following areas: Sustainable building systems or materials science Power system modeling, control systems, or HVAC alternatives IoT and sensor networks in the built
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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qualification; (ii) demonstrate research skills in imaging science and machine learning, particularly on image reverse engineering, fake image and video detection, statistical detection models and mathematical
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | 2 months ago
algorithm performance. You will analyze assignment data from December 2025 to the present to identify workload distribution patterns and refine the algorithm using mathematical modeling, programming, and
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, or related disciplines) Related Skills & Other Requirements Demonstrated abilities in mathematical modeling, analysis and/or scientific computation, scientific software and algorithm development, data analysis
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | 1 day ago
mathematical ADA model to provide quantitative immunogenicity assessment for therapeutic proteins. This model was constructed using antibody titer data from subjects across 10 clinical trials, with ADA time