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-efficient computing Developing mathematical modeling for complex scientific problems Designing algorithms to improve the performance of scientific applications Researching digital and post-digital computer
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
, or other novel/emerging pollutants - Developing / implementing advance machine learning algorithms for environmental datasets - Attention to detail and careful documentation of work products such as How
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sustainability. The selected researcher will contribute to the development of predictive models and machine learning algorithms for data analysis from plant-based sensors, multispectral and thermal imagery, and
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of malignancies, blood disorders, and experimental therapies. Job Summary The Data Science, Analyst will will work to maintain and deploy algorithms for accurate detection, segmentation, and classification of cells
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passionate about applying ML algorithms and developing AI applied research and innovation solutions using classic ML to novel transformer neural networks. We test and measure the real customer impact of each
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to multidisciplinary project teams, and develop broader research and engineering skills through mentorship and project-based experience. As New Mexico’s flagship R1 research university, UNM offers a collaborative and
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growth. Develops innovative solutions and novel approaches to space systems challenges, including new communication architectures, radiation mitigation strategies, advanced control algorithms
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will be expected to develop a nationally recognized, externally funded research program that is collaborative, interdisciplinary, and self-sustaining. The program should address critical challenges
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Research Infrastructure? No Offer Description Mission: Provide high-level scientific and technical advice for the line of research in Robot Personalization. Functions to be developed: Supervision
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-precision localization and radar-based sensing. You will develop adaptive algorithms that dynamically select the optimal radio configuration based on the specific requirements of each application. The radio