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implementing new informatics tools and resources to enhance phenotyping performance or enable deep phenotyping through terminology/ontology, natural language processing, and machine learning. The role involves
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. Knowledge or experience of Robot Operating System (ROS), tools for training and using deep learning algorithms and in image processing and computer vision algorithms and solutions using open-source software
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algorithm design and development of effective computing techniques To see examples of our innovative work please visit: https://www.ecshowcase.com/ What We're Looking For Education and Experience Needed
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, and ways of applying such foundational analysis for quantum technological or social benefit (e.g., through designing protocols or algorithms for, or building understanding of, quantum computing
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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algorithms in the field of welding technology. Joining three different metal sheets using resistance spot welding (RSW) presents researchers with challenges. We are tackling these as part of a public research
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. Department: Res Dept of Biomedical Computing. Contact details:Dr. Rachel Sparks. rachel.sparks@kcl.ac.uk Location: St Thomas Hospital. Category: Professional & Support Services. About Us We are seeking
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or Mathematics, Computer Science or another quantitative field, but higher qualifications (Master’s or PhD) is preferred. Excellent knowledge of at least one of the following scripting/programming languages
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suitable data models [CSC+23]. Objectives As far as the design of efficient numerical algorithms in an off-the-grid setting is concerned, the problem is challenging, since the optimization is defined in
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, algorithms, or computer science courses. Strong understanding of core data structures (e.g., arrays, linked lists, stacks, queues, trees, graphs, hash tables) and algorithms (e.g., sorting, searching, dynamic