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Research Associate to work on an industry-focused supply chain modelling and analytics project. The post-holder will have expertise in optimisation modeling, machine learning techniques, excellent
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of influential knowledge leadership bringing the School together with students, business and society in learning to make a difference. Over the last five years ULMS has engaged in extensive recruitment of academic
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) and bioinformatics tools Familiarity with data science, machine learning, artificial intelligence, natural language processing and applications to electronic health records and big data and
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expertise to investigate individual differences (that might predict learning and outcomes), underlying cognitive and neurobiological mechanisms, and intervention outcomes using tools including, but not
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machine learning are desirable, applicants from other quantitative fields (e.g. math, physics, statistics, computer science) who are eager to learn about neuroscience are highly encouraged to apply as well
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-level understanding of kinetics in solid-solid phase transitions; Develop advanced machine learning methods for the fast prediction of materials properties; Publish results in peer-reviewed journals and
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and other machine learning models (especially neural network models, time-series models) and coding in python and R. Strong collaborative skills and ability to work well in a complex, multidisciplinary
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the brain. We are particularly looking for a PhD level systems neuroscientist with expertise in animal behavior tracking using deep learning algorithms and its causal link with specific neural circuits
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networks; experience in applying machine learning models and processing imagery from UAS and satellite platforms. Other requirements: Willingness to work irregular hours and in occasionally adverse weather
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that incorporate latest machine-learning algorithms). Furthermore, the successful candidate will collaborate broadly with the other members of IO and CFN, leveraging their expertise in design and fabrication