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Cancer Registry, as part of the national SEER registries. The postdoc fellow will work closely with statisticians, computer scientists, oncologists, and epidemiologists in the lab and other collaborating
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languages such as Python, MATLAB, or C++, and experience with machine learning frameworks (e.g., TensorFlow, PyTorch) preferred. Familiarity with medical imaging processing and reconstruction techniques
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gases, including the operation of magneto-optical traps, the production of quantum degenerate gases and optical trapping using optical tweezers/lattices. They will be expected to display initiative and
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-of-the-art ground materials test facility tailored for hypersonic applications. Oversee the technical operation, training and usage of manufacturing equipment at ERAU for this project including
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Diseases (NIAID ) National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS ) National Institute of Biomedical Imaging and Bioengineering (NIBIB ) National Institute on Deafness and Other
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-EELS, STEM-EDS, electron diffraction, and 4D STEM, is essential. Experience with in situ gas phase TEM and low-dose imaging. Experience synthesizing polysiloxanes, processing thin polymer films, and
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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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in the near future) in Cancer Biology or a related field. Proficiency in experimental techniques such as cell/organoid culture, library construction, imaging and handling animal models. Experience in
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protected and open field cultivation systems Use lab and field equipment (ICP, HPLC, gas exchange analyzer, soil/root/plant sensors, chlorophyll fluorescence, etc.), data loggers and image processing tools
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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