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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
biological matrices. - Data Handling: Experience working with large datasets, particularly those derived from mass spectrometry-based analyses. - Independence & Problem Solving: Demonstrated ability to work
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for program information (e.g., Braille, large print, audiotape, American Sign Language, etc.) should contact the responsible Agency or USDA’s TARGET Center at (202) 720-2600 (voice and TTY) or contact USDA
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are also supported by funding from the NIH and NSF. The CompEpi group currently supports several CS PhD, Masters and undergraduate students. The post-doctoral scholar will have regular opportunities
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Category: Faculty University Authorized FTE: 100 Unit: AGNR-Plant Science & Landscape Architecture Campus/College Information: Founded in 1856, University of Maryland, College Park is the state’s flagship
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conditions, to large field-scale experiments with wild and domestic grazers. These experiments will test hypotheses related to the effects on nutrient cycling of grazers with different body size and grazing
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to build a collaborative scientific carrier in computer science and medical data analysis at a German top-ranked university. Help to acquire, mentor and teach students (e.g., PhD, MSc, BSc, seminar series
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Posting Information Posting Number FAE1493 Advertised Title Post-Doctoral Researcher, Computer Science Campus Location Main Campus (Memphis, TN) Position Number 023558 Category Full-Time Faculty
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with large-scale data analytics frameworks (Hadoop, Spark, Flink, etc.) is desired - Interest in the development of software systems, very good knowledge and skills in programming with standard
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models and neural networks that handle the many challenges of integrating such complex medical data sources on large-scale studies and the translation to clinical practice. Qualifications PhD in (Bio
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, please browse https://www.memphis.edu/fcbe . Minimum Position Qualifications Candidates must have a PhD or equivalent in a business or related field and experience in working with large datasets