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to quickly adapt to different environments and open to new processes and technologies. * Self-directed with a solutions-oriented attitude; values and inspires a positive work environment. * Ability to work
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meaning from data. Designing machine learning algorithms and undertaking testing for: predictive maintenance. operational performance and cost optimization. failure prevention and timely reparation of Aids
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initiatives to build and nurture the Dawn user community, convening workshops and networking events that bring together researchers from different disciplines and institutions. Mentorship: Design and deliver
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, and use smart phone apps to collect passive and active data using a prospective observational cohort study design. We will use this data to develop and validate a personalised risk prediction algorithm
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algorithms for analyzing electrocardiography, electromyography and movement signals, identifying characteristics and recognizing patterns in everyday activities. Testing and validation of methods developed in
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
/or machine learning/artificial intelligence algorithms. Projects may also include work focused on the analysis of spatial and geographic data and work extrapolating results to different spatial scales
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of the radio system. Interaction between different sub-parts is essential to reach a well working and efficient cellular or wireless communication system. This employment has a special focus on joint wireless
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mission is directly tied to the humanity, dignity and inherent value of each employee, patient, community member and supporter. Our commitment to learning across our differences and similarities make us
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the world are tackling global issues and making a difference to people's lives. We believe that inspiring our people to do outstanding things at Durham enables Durham people to do outstanding things in
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are in particular targeting development of data-driven high-performance computing techniques for unbiased discovery of generative models & theory and algorithms for network inference with special reference