57 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Duke University in United States
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Computer Science and Electrical and Computer Engineering departments, and the School of Medicine. The group emphasizes collaborative and multidisciplinary work and brings together expertise from machine learning
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with various methods that can incorporate domain-based constraints and other types of domain knowledge into machine learning and applying these techniques to problems in computational creativity
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. The Postdoctoral Associate will apply his/her technical skills toward development and implementation of machine learning, computer vision, and other algorithms for analysis of medical images and prognostication as
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biology, computational biology, and animal medicine. With these expertises, the DHVI is working collaboratively to develop vaccines and countermeasures against pathogens like HIV, SARS-CoV-2, and influenza
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computational and data analytical methodology development and implementation; experience in supervised and unsupervised machine learning, low-dimensional models or deep learning models, and willingness to learn
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Training Program. This position will be funded by our NIDDK T32. Eligibility: U.S. citizenship or permanent residency required PhD applicants must have been awarded their degree or anticipated prior to June
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a PhD or equivalent doctorate (e.g.ScD, MD, DVM). Candidates with non-US degrees may be required to provide proof of degree equivalency.1. A candidate may also be appointed to a postdoctoral position
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independent research activities under the guidance of a faculty mentor, Shyni Varghese, PhD, in preparation for a full time academic or research career. The job includes fabrication and characterization
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a PhD or equivalent doctorate (e.g.ScD, MD, DVM). Candidates with non-US degrees may be required to provide proof of degree equivalency.1. A candidate may also be appointed to a postdoctoral position
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of output from global climate models (CMIP-class models) as well as Integrated Assessment Models (IAMs) such as GCAM or PAGE. The candidate must have a PhD degree in a related field, be fluent in computer