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Fluorescence, FRET, & single‑molecule microscopy Mechanobiology, force-spectroscopy Bioconjugation chemistry, nucleic‑acid chemistry Quantitative image analysis, MATLAB/Python scripting, or machine learning
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McGill University | Winnipeg Sargent Park Daniel McIntyre Inkster SE, Manitoba | Canada | about 2 months ago
fluorescence data. Developing machine learning methods to optimize data collection. In addition, the project is committed to developing open source tools that benefit the imaging community. The applicant will
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medical machine learning for a talented postdoctoral researcher (f/m/d) to deepen their expertise and interest in machine learning for medical image analysis and build their early scientific career. About
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the pre- and post-processing of Magnetic Resonance (MR) images (or utilization of existing brain imaging markers), taking peripheral or central biomarkers, and regressing them against those images using
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Current Employees: If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how
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The X-ray Imaging Group (IMG) at the Advanced Photon Source (APS) is seeking a postdoctoral researcher with expertise in biomedical imaging and image processing to develop advanced processing
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Researcher / Postdoc for molecular investigations on microbial ecology in deep-sea polymetallic n...
Qualifications and Skills Knowledge of microbial metabolic processes and methods to study them (e.g., tracer-based incubations) and general marine/benthic biogeochemistry Interest and intention to acquire and
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developing novel analytical methods for studying the development and degeneration of the visual system Acquire, process, integrate, and standardize large-scale multi-omics datasets and build databases Perform
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an unprecedented corpus of newspaper and radio archives, Impresso - Media Monitoring of the Past (https://impresso-project.ch/ ) is an interdisciplinary research project that uses machine learning to pursue a
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on two core but complementary areas: Computer vision and sensor data analysis, applied to tasks such as object detection in drone images (e.g., pest or disease detection), object tracking (e.g. leaves