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within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer
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to shape behavior. Brainard and his team want to understand how the nervous system changes over the course of development to give rise to critical periods for learning, and how individuals’ innate variations
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, applications of machine learning to particle phenomenology, and lattice QCD, both within the Standard Model and beyond. The particle physics phenomenology group members are: J. F. Kamenik (head), B. Bajc, S
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research teams that include faculty, graduate students, and undergraduate students. One student’s research used machine learning to solve physics problems, while another’s helped create a data science
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Toggle navigation Your VUSM Current Students Postdocs Residents Basic Sciences Faculty Affairs Clinical Faculty Affairs Alumni Patients A-Z Directory VUSM Catalog School of Medicine Vanderbilt
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
large data set types including RNAseq, DNAseq, RIPseq, and CLIPseq. Experience in gene expression analysis, alternative splicing analysis, machine learning, and motif analysis are preferred. Candidates
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Postdoc Appointment Term: 2 year renewable Appointment Start Date: As early as summer 2025 Group or Departmental Website: http://www.staarlab.com (link is external) How to Submit Application Materials
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knowledge of digital image processing, are helpful Basic knowledge fpr application of artificial intelligence and machine learning methods Creativity and ability to work independently in a scientific
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periods for learning, and how individuals’ innate variations interact with experience to give rise to differences in learned behaviors. The team focuses on vocal learning in songbirds as a model system to
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transitions and universality for spectral statistics of random matrices and their applications in high-dimensional statistics, machine learning and probability theory. The Department of Mathematics at KTH