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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 19 hours ago
is also leading the development and validation of novel machine learning methods for LEGEND simulations and analysis. We have been heavily involved in constructing, commissioning, and operating
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, earth or energy. Learn more at www.hds-lee.de . Institute specific promise here. We are looking to recruit a PhD position – Co-regulation structures for large-scale single-cell transcriptomics – within
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knowledge of power system security and machine learning being crucial. The Associate will primarily work alongside National Grid engineers to integrate the machine learning backend of the intrusion detection
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Intelligence and machine-learning approaches and emerging digital technologies such as non-contact sensors, smartphones, and computer tablets. This theme could also include research in data analytics and
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. Teaching skills. Additional assessment criteria: A strong ability to develop and conduct high-quality research independently. Experience using deep learning methods and computer vision with biological data
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data integration data quality data analytics programming languages (SQL, Python, Java) Complementary IT skills: machine learning image recognition sensor technologies robotic technologies
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, applications, tools, and services for the broader research community to use data at scale to pursue scientific inquiry and accelerate discovery. Learn more at https://gdc.cancer.gov/ , https://gen3.org/ , https
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team. Find more information about the Strategic Management area and its members here: http://strategy.univie.ac.at What you will be doing: In addition to their research work, candidates assist and
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diffraction data where the information extends towards 3-d space. Machine learning offers promising approaches for the solution of complex problems of disorder, ultimately aiming at general and automated
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participant outcomes. The project will use a variety of approaches, including human perceptual experiments, machine learning, digital signal processing, and computational models of hearing. UConn has a vibrant