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, evolutionary biology, computer science, physics, applied mathematics, or engineering. Our research integrates mathematical modeling, machine learning, and quantitative experiments to understand and control
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the Interpretable Machine Learning Lab (https://users.cs.duke.edu/~cynthia/home.html ) for a scientific developer to work in collaboration with other researchers on machine learning tools that help humans make better
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to student learning, research, health care, and service is seeking applicants for a postdoctoral fellow position in the Department of Pediatrics, Division of Medical Genetics. The candidate will join a dynamic
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of natural language processing, machine learning, artificial intelligence, and human-computer interaction. Established within the School of Computer Science, LTI pioneers innovative approaches to understanding
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 6 hours ago
biogeochemical model using times series forecasting and machine learning. The Post Doc will focus on one or two of the questions depending on their expertise and interest. Minimum Acceptable Education & Experience
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Investigator Dr. Ji Liu in the department of Electrical and Computer Engineering . The incumbent will conduct research and ensure that all experiments are appropriately conducted following the policies and
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in University programs, services, and activities. Syracuse University has a long history of engaging veterans and the military-connected community through its educational programs, community outreach
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have experience in computational neuroscience and data mining using machine learning methods. The successful candidate will lead an independent research project dedicated to identifying abnormal neuronal
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of natural language processing, machine learning, artificial intelligence, and human-computer interaction. Established within the School of Computer Science, LTI pioneers innovative approaches to understanding
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the intersection of machine learning and genomics. The project involves the development and application of advanced machine learning and deep learning techniques to understand the sequence-function relationships