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Field
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Skills General office suite and willingness to learn lab specific programs Supervisory Responsibilities No Required operation of university owned vehicles No Does this position require direct animal or
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, Physics, Engineering, or a related field, earned within the past six years Experience with AI and machine learning Excellent written and spoken communication skills Demonstrated ability to produce high
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Neuroscience on object representation and object properties using machine learning and multivariate techniques to analyze the data; support in writing scientific outputs. The grantee will also support the entire
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Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. Your work may include clinical and biomedical projects. It may also include technique development
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morphology (e.g., geometric morphometrics, machine learning), and phylogenetic comparative approaches. We have: • An engaging, supportive, and collaborative research environment. • Opportunities
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systems. Combination of behavior with large-scale neural recordings using silicon probes, miniscope, or 2P imaging. Ability to explore and analyze large datasets using modern machine learning methods and a
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 19 hours ago
the development and implementation of machine learning models Special Physical/Mental Requirements Special Instructions For information on UNC Postdoctoral Benefits and Services click here Quick Link https
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activities. Qualifications: Ph.D. in Bioinformatics, Computational Biology, Computer Science, Genomics, or a related field. Strong background in machine learning, particularly deep learning and natural
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contribute to projects using cutting-edge molecular, cellular, and spatial profiling approaches to dissect vascular and immune signaling across injury models. Key technologies and methodologies include
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at the intersection of scientific computing and machine learning. At a high level, the project is to build neural network models of potentials that appear in Hamiltonians for time-dependent quantum systems. The postdoc