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requires not only expertise in LLMs and machine learning but also an understanding of the unique challenges posed by scientific data, which often includes large-scale numerical datasets, complex simulations
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Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) PhD (or foreign equivalent) in Biomedical Engineering, Medical Physics, Electrical, Computer Engineering or a
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, or MATLAB) are required. Knowledge in one or more of the following areas is desirable: biomedical imaging, biomedical optics, computer vision, bioinformatics, single-cell profiling technologies, spatial omics
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integrated circuits (IC) and printed circuit boards (PCB). Additionally, the candidate should demonstrate expertise in applying computer vision, image analysis techniques, machine learning, deep learning to IC
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diseases, functional connectivity, graph theoretic, &/or machine-learning based approaches to imaging analysis are all a plus. • There will be a significant amount of flexibility based on the post doc’s
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model APIs, cloud computing environments, and R for additional statistical analysis. For decision support prototype development and evaluation, web-based user interface design, human-computer interaction
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
of microscopy and imaging techniques is a plus. Willingness to learn new in vivo and in vitro techniques, such as performing animal surgeries, intra-muscular, intra-articular and intravenous injections
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, research, and public service. Job Description Purpose: The Department of Electrical and Computer Engineering and AggieFab Nanofabrication Facility at Texas A&M University seeks a Postdoctoral Researcher to
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optimizing the squeezing of the vacuum to minimize quantum noise, a prototype cryogenic interferometer, using machine learning for nonlinear feedback control, devising techniques to quell opto-mechanical
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Posting Details Posting Details Posting Number 0801675 Classification Title Postdoctoral Research Associate- Autonomous Systems and Machine Learning Working Title Department College