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Field
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to apply tensiomyography and ultrasound to evaluate skeletal muscle structure and function, able to analyze MRI images of skeletal muscles ○ Image analysis: quantify muscle architecture and fat fraction
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downstream signaling. These findings have shifted the paradigm on how biological specificity is achieved to generate unique responses downstream of PDGFR engagement. Available projects will utilize novel PDGFR
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subject. Proven experience with X-ray imaging/diffraction techniques, e.g. XRD-CT, 3D-XRD, µ/nanoCT, STXM or similar. Experience in computer programming for data analysis, e.g. Python. Demonstrated ability
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: Communication, teamwork and collaboration, commitment, proactivity, integrity, and critical/analytical thinking. High level of English. Advantageous: Experience in nanomedicine, active matter, biomaterials, or 3D
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, or 3D cell culture models. Experience with in vivo imaging. Competencies and Skills: We value not only technical expertise but also the demonstration of core competencies such as Communication, Teamwork
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) and statistical genetics (GWAS, PRS, etc.) and related tools (e.g., PLINK). Experience with either 3D image processing (e.g., brain PET and MRI analysis) or statistical genomics (GWAS, PRS calculation
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resolution. As part of the Department of Bionanoscience and the Kavli Institute of Nanoscience, we enjoy access to state-of-the-art infrastructure for biochemistry, molecular imaging, cryoEM/ET and high
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implementing BCDI, XPCS, nano-beam and time resolved microscopy, PDF, 3D imaging techniques, PCI, and other techniques for advanced characterization of materials across solid-liquid and into melt. Measurements
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 2 months ago
application to gas hydrate system to develop efficient key parameter estimation tools and large-scale 3D geologic model for gas hydrate reservoir. Learning opportunities will be given on the area of laboratory
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 11 hours ago
migration in porous media under in situ conditions, and • Machine learning application to gas hydrate system to develop efficient key parameter estimation tools and large-scale 3D geologic model for gas