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or equivalent Skills/Qualifications The post-doc is expected to independently design, plan and conduct experiments. In addition, will oversee the work of the PhD student. Responsibilities: -To develop algorithms
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
is designed for candidates who have completed their PhD within the last two years and have experience as postdocs or industry researchers. This position offers a 12-month term with potential
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Basic qualifications (required at time of application) PhD or equivalent international degree, or enrolled in a PhD or equivalent international degree granting program Additional qualifications (required
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Foundation RECRUIT grant ("Data Management, Algorithms, & Machine Learning for Emerging Problems in Large Networks – with Interdisciplinary Applications in Life & Health Sciences". NNF22OC0072415
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to vertical flow immunoassays. (VFI). Experience in liquid nanoprinting of VFI membranes and design of experiments algorithms to simulate accelerated shelf-life testing is required. Applicants should be detail
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devices related to vertical flow immunoassays. (VFI). Experience in liquid nanoprinting of VFI membranes and design of experiments algorithms to simulate accelerated shelf-life testing is required
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the review process. You may upload these documents to the application under CV/Resume. Required education and experience Appropriate PhD in a related field. Physical Requirements Must be capable
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to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a
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will develop algorithms and methods aimed at better detection and mitigation of GNSS interference events from either jamming or spoofing attempts. In addition to research within GNSS integrity
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of auditory stimuli and creation of stimulation sequences 5) Implementation of pilot studies in adults and infants 6) Programming analysis algorithms for FFR, MMN and statistical learning, based on spectral and