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Professional Master’s degree or PhD degree in computer science, data science, biomedical engineering, imaging or related discipline such as mathematics, engineering or physics Proven track record of publications
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Guidelines . Assistant Professor Candidates must possess a PharmD, PhD, or MD or equivalent degree. Demonstrated expertise in one of the target areas as evidenced by a strong publication record or potential
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. Perform experiments in yeast and mammalian cells. Techniques include tissue culture, western blotting, DNA analysis, live cell imaging, and cloning. Analyze data and interpret experimental results
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cutting edge technologies incorporating techniques such as in vivo Ca2+ imaging, electrophysiology, bioengineering, brain computer/machine interfaces, neuromodulation and/or computational approaches
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organoid platform. Experience with cell-based workflows, imaging, or clinical sample–derived cultures. Applicants must meet minimum qualifications at the time of hire. Preferred Qualifications: PhD in
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of digital imaging systems such as whole slide imaging, telepathology and digital image analysis software · Collaborate closely with LIS, IT, laboratory, integrated practice and departmental staff as
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related to developing and applying contrast-enhanced ultrasound approaches, and image processing to study remodeling of the islet microvasculature and islet blood flow regulation in type1 diabetes and to
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laboratory of Andrew Bubak, PhD. The lab is funded by grants from the National Institute of Health and philanthropic organizations and investigates alphaherpesvirus infections of the central nervous system and
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Molecular Genetics at the University of Colorado School of Medicine. We study how cells detect and degrade aberrant RNAs, and how dysregulation of this surveillance process contributes to human disease
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, and formulation of clinical study design, image processing, machine learning, and statistical analyses to illuminate specific research questions. Among the machine learning techniques, deep learning