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Field
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language processing, machine learning, artificial intelligence, and human-computer interaction. Established within the School of Computer Science, LTI pioneers innovative ways to understanding, processing, and
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deployment. Experience with reinforcement learning (RL), computer vision, and sim-to-real transfer. Experience with robotic hardware platforms such as mobile robots, robotic arms, and embedded sensors
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Staff Job Description Required Education: Ph.D. in Biochemistry Preferred Experience: Prior experience with AlphaFold and other machine learning approaches are required. Required skills, knowledge
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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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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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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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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 1 hour 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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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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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