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Field
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transportation systems? We have an exciting opportunity to do just that in one of the UK’s most dynamic centres for engineering research and education. Working with industrial partners, you will develop and
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advantageous. Proficiency in algorithm development using Python will be advantageous Where to apply Website https://www.timeshighereducation.com/unijobs/listing/398927/research-fellow-ai-… Requirements
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& Other Requirements Demonstrated abilities in mathematical modeling, analysis and/or scientific computation, scientific software and algorithm development, data analysis and inference, and image analysis
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to migration-related diversity. The position contributes to advancing methodological innovation through the creative and reliable use of machine learning, AI, and other algorithmic techniques in qualitative
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, analysis and/or scientific computation, scientific software and algorithm development, data analysis and inference, and image analysis Ability to do original and outstanding research in computational biology
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and/or scientific computation, scientific software and algorithm development, data analysis and inference, and image analysis Ability to do original and outstanding research in computational biology
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Council and UNSW Sydney. The project seeks to advance the analysis of dynamical systems through the development of novel techniques in functional analysis, operator theory, ergodic theory, differential
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only within dense, highly interacting systems, inaccessible to standard techniques. To probe such regimes requires the development of fast and scalable algorithms for many-component systems, and of
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, scientific computation, scientific software and algorithm development, mathematical modeling, data analysis and inference, and image analysis Ability to do original and outstanding research in computational
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of this role is to support and contribute to an industry innovation research project. The Research Engineer will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep