1,208 computer-science-programming-languages-"Prof"-"Durham-University"-"Prof" Fellowship positions in United States
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processing, and sensor integration. Strong background in signal processing, computer vision, or machine learning. Proficient in programming languages such as Python, C++, and MATLAB. Strong publication record
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biostatistical, health data science, and informatics research and education. We have an extensive portfolio of research program in related areas. Our NIH funding as principal investigators and co-investigators has
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that machine learning applications are developed with ethical considerations in mind. Participate in regular meetings with the research group. Required Qualifications* Ph.D. in Electrical Engineering, Computer
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Qualifications Ph.D. or M.D./Ph.D. in areas such as bioengineering, biochemistry, cell or computational biology or related fields Additional Qualifications CV Research summary of PhD work Cover letter describing
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experience. The anticipated annual stipend is $77,274 with a health insurance supplement. Citizenship Requirements: This opportunity is available to U.S. citizens only. ORISE Information: This program
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-fellowship/surgical-pathologyclinical-informatics-fellowship , for detailed information on the Surgical Pathology/Clinical Informatics fellowship. For questions regarding the program(s), please contact
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Posting Information Posting Number FAE1908 Advertised Title Postdoctoral Fellow in Machine Learning and Computational Biology Campus Location Main Campus (Memphis, TN) Position Number 023825
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The Position We advance science so that we all have more time with the people we love. A position is available for a postdoctoral fellow to join the Genentech Computational Sciences (gCS
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date) in Data Science, Computer Science, Statistics, Environmental Science, Sustainability Studies, or a related field with a strong quantitative focus. Applicants with an interdisciplinary degree
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, together with significant experience in computer programming and computational biological applications. A strong background in statistics and biology. Formal training and/or research experience in genomics